Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Session Overview
Date: Monday, 26/Jun/2017
6:00pm - 8:00pmWelcome Reception
Complesso San Geminiano 
Date: Tuesday, 27/Jun/2017
8:30am - 9:00amRegistration & Welcome Coffee
Complesso San Geminiano 
9:00am - 10:00amOPENING: Opening Ceremony
Session Chair: Marcello Pellicciari
Session Chair: Margherita Peruzzini
Marcello Pellicciari (University of Modena and Reggio Emilia, Italy)
Munir Ahmad (Teesside University, UK)
Aula Convegni (first floor) 
10:00am - 10:55amKEY 1: Keynote Speech 1 (Franco CEVOLINI)
From Racetrack to Road - How CRP Group and Windform® composite SLS materials drive manufacturing
Aula Convegni (first floor) 
10:55am - 11:20amCoffee break
Gallery at first floor 
11:20am - 1:00pmSES 1.1: Data science in manufacturing
Session Chair: Chia-Yen Lee
Aula Convegni (first floor) 
 

261. A conceptual framework for “Industry 3.5” to empower intelligent manufacturing in emerging countries and case studies

Chen-Fu Chien

National Tsing Hua University, Taiwan

Leading nations have reemphasized manufacturing with national competitive strategies such as Industry 4.0. The paradigm of production and manufacturing system is shifting, in which the increasing adoption of intelligent equipment and robotics, Internet of Things (IOT), and big data analytics have empowered manufacturing intelligence. Leading companies are battling for dominant positions in this newly created arena via providing novel value-proposition solutions and/or employing new technologies to enhance smart production. However, most of emerging countries may not ready for the migration of Industry 4.0. This study aims to propose a conceptual framework of “Industry 3.5” as a hybrid strategy between Industry 3.0 and to-be Industry 4.0, to address some of the needs for flexible decisions and smart production in Industry 4.0. Empirical studies in high-tech manufacturing and other industries are used for illustration. Future research directions are discussed to implement the proposed Industry 3.5 to facilitate the migration of Industry 4.0.


51. Equipment Health Monitoring in the Semiconductor Assembly Process

Zhao-Hong Dong, Bo-Kai Jang, Chia-Yen Lee

National Cheng Kung University, Taiwan

Due to the semiconductor assembly process is capital-intensive for mass production, the industry faces a major challenge of management issue─ monitoring the thousands of equipment. In general, overall equipment effectiveness (OEE) has been widely used to measure the productivity and assess the status of equipment. However, there are some other indices not identified according to the OEE, for example, the usage of consumables and spare parts. This study proposed an equipment health monitoring (EHM) framework to improve the OEE, drive the productivity, and support preventive maintenance. The EHM framework has several modules including the data preprocessing, statistical process control (SPC), analytic hierarchical process (AHP), and finally provides an equipment health index (EHI) of the equipment. According to different types of the status variable identifications (SVIDs), several SPC control charts are developed to monitor each SVID individually and the weight of each SVID is extracted to build the EHI via AHP method. An empirical study of the Taiwan leading semiconductor assembly manufacturer is conducted to validate the proposed models. The result shows that the proposed framework supports the real-time monitoring of equipment health in the thousands of equipment. When EHI decreases and equipment alarms, the firm can trace the root cause by the decomposition of EHI for trouble-shooting.


61. Work Study and Simulation Optimization of Supply-Demand Balancing in the Moth Orchid Plant Factory

Jia-Ying Cai, Chin-Yi Tseng, Ting-Syun Huang

National Cheg Kung University, Taiwan, Taiwan

During the four-year production lead-time, some inevitable factors (e.g., insect pest, plant disease) might have a negative impact on the quality of Phalaenopsis (i.e., moth orchids); besides, the market fluctuation results in difficulties of decision-making and unstable income of the company. This study develops a two-stage framework which investigates the production process in the 1st stage and balance the supply and demand in the 2nd stage. An empirical study of a moth orchid plant factory is conducted. The first part we use time motion study to build up operator process chart and process sequence. Based on the lean production management, we identify seven muda (e.g., transportation waste, inventory waste, etc.) and eliminate them. Thus, the standard operating procedures (SOP) can be developed for the plant factory. In the second part, we build up a simulation model of the production process via the SOP. We use the production input and output collected data to figure out the variable parameters (e.g., yield). We also collect the global moth orchid market supply distribution and decompose the market share to the case factory to know the supply distribution of the case factory (i.e., global market share of the case factory). According to the decomposed supply distribution as our output distribution into the model, we can obtain the input portfolio with minimal cost by simulation optimization technique to address the demand-supply mismatching problem.


117. Development of a process data-based strategy for conditioning position-controlled ID cut-off grinding wheels in silicon wafer manufacturing

Uwe Teicher, Wolfgang Dietz, Andreas Nestler, Alexander Brosius

Technische Universität Dresden, Germany

Manufacturing technologies in the semiconductor industry put high demands on accuracy and process reliability, which is reflected in high manufacturing costs. Particular attention has to be paid to the initial steps of wafering, as these processes can significantly help in determining important quality parameters and can have a strong economic influence on subsequent processes.

ID grinding has established itself as a cost-effective manufacturing method for the production of wafers with a diameter of up to 150 mm. Further developments in mechanical engineering aimed at improving the quality parameters TTV and Bow, resulted in the integration of a magnetic position control, which specifically influences the axial position of the grinding wheel and thus also the position of the abrasive layer in the grinding gap. However, applying the position control results in a modified scenario for the conditioning of the grinding wheel, since control signals for activating a conditioning measure can no longer be used.

The approach to solving this problem, is to develop a conditioning strategy which is, on the one hand, based on data provided by the grinding machine. On the other hand, it also describes which signals - generated by a process computer for position control - are being processed, evaluated and made available to the grinding machine.

As a result, an operational manufacturing solution is presented, which can help to improve the performance of position control in connection with a modified strategy for the conditioning of the abrasive layer in order to improve the quality parameters of IC wafers.

 
11:20am - 1:00pmSES 1.2: Production Planning and Scheduling
Session Chair: Sang Won Yoon
Aula N (first floor) 
 

129. Solving a multi-periods job-shop scheduling problem using a generic decision support tool

Cristovao Silva, Nathalie Klement

ENSAM, France

In this paper we present a generic decision support tool which was developed to solve many different planning problems. The proposed tool consists of a hybridization of a metaheuristic and a list algorithm. The metaheuristics can be used without any changes independently of the problem to be solved. The list algorithm must be adapted according to the studied problem. Thus, the proposed tool can support the decision process for several different planning problems with a minimum development work.

The described decision support tool was already tested with two different planning problems: (1) an activities planning and resources assignment problem in a multi-place hospital context and (2) a lot-sizing and scheduling problem with setups and due dates, for a plastic injection company. In both cases good results were obtained with the proposed tool.

In this paper we intend to present the developed tool and to describe its application to a new problem, a multi-periods job-shop scheduling, proposed by a case study company which produce industrial refrigeration equipment’s.

In the case study company, a set of metallic components are to be produced to satisfy the demand of an assembly line. Each component has to follow a processing sequence to be produced and each operation in this sequence requires a given resource (machine). The planning horizon is a week which is divided in five periods of one day. To satisfy the demand from the assembly line, a set of different lots of components is to be produced in each day of the planning horizon. Thus, we have a set of N jobs which have to be processed on a set of M machines. Each job is defined by a sequence of operations that are associated with a particular machine. Each operation has a processing time and there is a setup time between the processing of two consecutive operations which is sequence dependent. Each job has a requested period. We consider a penalty function, composed by two parts: (1) a storage cost (earliness) if the job is produced in a period prior to the requested one, (2) a tardiness cost if the job is produced in a period after the requested one. The objective is to define the operations sequence in each machine in order to minimize the total penalty.

A list algorithm is presented to be used by the tool to solve the described problem and data from the case study company were collected to generate a test instance. The decision support tool, considering the generic metaheuristic and the developed list algorithm is tested using the generated instance. The test results are presented and the ability of the proposed tool to deal with the case study company planning problem is discussed.


29. A cardinality-constrained approach for robust machine loading problems

Giovanni Lugaresi, Ettore Lanzarone, Nicla Frigerio, Andrea Matta

Politecnico di Milano, Italy

The Machine Loading Problem (MLP) refers to the allocation of operative tasks and tools to machines. Several deterministic models have been proposed in the literature for solving the MLP. However, processing times are strongly affected by uncertainty due to a variety of sources, e.g., failures, unexpected tool breaks, and unplanned maintenance interventions. As a consequence, the quality of the solution in terms of system performance is deteriorated, as the actual behavior of the system may highly differ from expectations. Thus, appropriate robust methods should be used to overcome this issue, even though the literature on robust models is scarce.

We propose a robust formulation for the MLP, with the goal of evaluating throughput bounds in the presence of a fixed number of unfortunate events over a given planning horizon. Each event is modeled as an increase of the actual processing time with respect to the nominal one, which represents the machine failure. The bounds are due to the fact that the same number of events may have a different impact on system performance, depending on how they are arranged.

The robust model proposed for the upper bound is based on the cardinality-constrained approach, in which a parameter Gamma for each tool represents the number of processing times that vary from the nominal to the maximum value due to an unfortunate event. Thus, robustness is tuned by giving a budget to the number of unfortunate events that affect each tool. The pattern of events that mostly deteriorates the system throughput is selected, and the solution is provided for this pattern, i.e., the model generates the production plan and machine tools allocations that better protect from the Gamma unfortunate events. Such robust plan can support production managers with an accurate estimation of the minimum production level that a certain system achieves in the worst conditions.

A set of realistic instances is generated to validate the robust MLP model, by tuning the size of the problem (e.g., number of produced parts, number of tools, time horizon) and the number of events in the given time horizon. The outcomes show that the objective function fairly decreases with the increase of the number of unfortunate events that affect the system. Low computational times allow the applicability in the practice. Further, this is the first application of the cardinality-constrained approach to MLP.


330. Hierarchical Sequencing of Operations with Consideration of Setups

Mayur Wakhare, Dusan Sormaz

Ohio University, United States of America

Generative Modelling methods are becoming more popular. Despite the fast and dynamic development of CAx systems, well-described procedures of Generative Model creation do not exist. The lack of the described systems and their methodologies means that only a small group of engineers have knowledge and experience to create and use such type of models. In this paper, the authors try to highlight two methods of Generative Model preparation. These methods are the results of the authors’ experiences in working with such types of models. The first method is based on cooperation with external models which are input elements into a Generative Model. Input elements (geometrical or parametrical) are one of the most important things in the process of automatic model generation. The second described method is based on an input element in a wireframe form. The paper highlights areas of application and some advantages and disadvantages for each of the presented methods.


222. Improving the Efficiency of Large Manufacturing Assembly Plants

David Sly, Michael Helwig, Guiping Hu

Proplanner, United States of America

Large manufacturing assembly plants with sub assembly lines, sequenced material deliveries, and batch driven primary manufacturing operations often struggle with coordinating their sequenced part manufacturing and kitting operations with the dynamic constraints of the main final assembly line. Additional challenges arise from the many disconnected information streams available to each group which provide delayed information with not enough part and location specific details.

Iowa State University (ISU), Proplanner and Factory Right partnered with a major Aircraft manufacturer and also a major Industrial/Ag Equipment maker to address this specific challenge with a product called Factboard. The team is being supported by the United States Army via the Digital Manufacturing and Design Innovation Institute (DMDII). DMDII is a federally-funded research and development organization of UI LABS, with a goal of increasing efficiencies of factories throughout the United States.

Making improper decisions with incomplete data reduces a factory’s throughput rate, and can result in substantial inventory increases and low overall equipment effectiveness. Pilot studies of Factboard components have demonstrated 98% reductions in line stoppages due to logistics issues, 86% reductions in on-site inventory, and 50% reductions in indirect material handling labor, all while simultaneously increasing productive throughput by nearly 10%. All of this contributes to reducing operational costs and increasing the ability of the factory and its supply chain to respond faster to changes in requirements.

A key innovation of Factboard is its ability to utilize existing transactional data within the enterprise and dynamically respond to increases, or even temporary decreases, in the quantity and quality of these real-time inputs. Because companies are often not in a position to make major upfront investments in shop floor data collection, Factboard can utilize the available information and attempt to fill in the holes to provide a real-time picture of “current events” occurring within the production systems internal to, and supplying, the final assembly line.

This is accomplished by Factboard’s ability to map engineering production life-cycle management (PLM) data sets with factory-specific build schedules and real-time transactional production and logistics data to create a series of information-rich and visually effective views designed around the needs of shop floor personas (user-defined dashboard views of production). Factboard’s decision support engine then provides specific calculations and probabilistic recommendations about inventory and resource availability at multiple points within the production system.

This paper and presentation will outline the high level data model, workflow and use-case scenarios of how the Factboard system integrates into the factory’s engineering and transactional data sources as well as how users have been able to use this more accurate, detailed and timely information to make better decisions.


189. A Heuristic Algorithm to Balance Workloads of High-Speed SMT Machines in a PCB Assembly Line

Tian He, Debiao Li, Sang Won Yoon

State University of New York at Binghamton, United States of America

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11:20am - 1:00pmSES 1.3: Additive Manufacturing
Session Chair: Dong-Won Kim
Aula O (first floor) 
 

156. Transient thermo-mechanical modelling of stress evolution and re-melt volume fraction in electron beam additive manufacturing process

Rani Kasinathan Adhitan, Nagarajan Raghavan

Singapore University of Technology and Design, Singapore

Electron beam melting and selective laser melting processes are in demand because of their capability to produce highly dense and homogeneous structures. The quality of parts produced using powder bed fusion additive manufacturing processes mainly depends on the energy source, raster scan pattern, and stress evolution due to concentrated heat addition. Also, the study on temperature profile over the scanning period is important as it accounts for the energy build up that pre-heats the material in-front of the scan head. The amount of raw powder material that has been converted to bulk solid upon melting - solidification cycle is governed by the penetration depth of the energy source and the absorption profile. In order to analyze the relationship between these various process parameters such as input power, penetration depth, raster scan hatch spacing, powder porosity and their effects on the temperature profile, stress evolution and re-melt volume, a three-dimensional thermo-mechanical simulation of the EBAM process on AISI 316L stainless steel is implemented using the COMSOL® multiphysics modelling platform. The phase changes are modeled using the apparent heat capacity method. With an effort to improve the accuracy of the modeling results, temperature dependent thermo-mechanical properties are incorporated. Also, linear, and exponential thermal absorption profiles are considered and their results are compared in-terms of amount of re-melt volume and stresses. Our results show that the hatch spacing plays a critical role in governing the temperature distribution and the residual stress patterns in the solidified regions of the substrate. The volume fraction of re-melt materials shows a non-linear and non-monotonic dependence on the electron beam size. The plot of stress evolution at a point located at the end of raster shows a double peak and valley as the beam approaches it and moves away during the second raster. The first peak is observed when the powder is about to melt as it experiences sudden rise in temperature. The valley represents the drop-in stress levels due to elevation of temperature above the melting point. When the beam head moves away, the second peak is observed because of re-solidification and temperature contours that are close to the melting temperature. Affected by the cumulative thermal budget buildup, the region around the raster turn experiences maximum residual stress. The peak temperature in the substrate is attained at the start of the scanning process and drops subsequently as the scan head moves further, which is supported by the rise in thermal conductivity of the re-solidified bulk material. The results of this study pave way for further robust design of the EBAM process from a simulation point of view.


127. Filament Temperature Dynamics in Fused Deposition Modelling and Outlook for Control

David Pollard, Carwyn Ward, Guido Herrmann, Julie Etches

University of Bristol, United Kingdom

Additive Manufacturing (AM) is a collection of processes capable of building solid objects directly from a computer-based geometry file. Through construction of the objects on a layer-by-layer approach, complex and functional geometries are easily achievable. Such components are often impossible to manufacture through conventional subtractive methods, due to internal geometries and material gradations. As virtually no different tooling is required, AM processes are ideally suited for customised components in small production runs.

Fused Deposition Modelling (FDM) is an AM process involving the extrusion of molten plastic through a nozzle moving relative to the print bed; usually affixed to a gantry system. This process is commonly used on low-cost 3D printers, but an increasing availability of higher strength and reinforced filaments has motivated research into its applications within the manufacturing sector.

Extensive work has been conducted on topological and process parameter optimisation. The valuable work in these fields has created tools for designing and manufacturing components with potentially superior properties to conventionally manufacturable parts.

For adoption into the supply chain for aerospace components, quality control systems must be implemented to ensure manufacturing consistency. Previous studies have researched feedback for improved control over the XY gantry, pre-emptive correction of thermal distortion, and iterative learning processes for road deposition widths at features. There have been efforts to model the extrusion process, but very little work has been conducted on the filament temperature change during flow rate variations. This parameter is key to ensuring good bonding throughout the component. A majority of modern extruder temperatures are controlled through a thermistor mounted within the heater block, assuming the filament will be extruded at the same temperature.

This paper investigates the effect of filament temperature on bond formation, and errors incurred through fluctuations during a typical printing process. During the build process, the filament flow rate rapidly changes, especially during the initial section of the deposited road. The extruded temperature was monitored by both a thermal camera and a nozzle-mounted thermistor, providing information on the fluctuations in extruded filament temperature. The printer nozzle test setup was driven through a fast prototyping DSpace system to allow efficient real-time measurement and control. Initial results have shown a step increase in flow rate from 6.4mm2s-1 to 31.9mm2s-1 causes a 15°C drop in extrusion temperature; with a predicted 30% reduction in sintering bond formation. Tests will be conducted to identify if this effect is mitigated through control of the nozzle temperature, as opposed to the standard block temperature controller. Further investigations will study the effect of retraction and priming motions on the extruded filament temperature.

The models herein developed provide an insight into the effect of flow rate variation on temperature, and subsequently bond quality, to enable potential weak spots in a structure to be identified. This represents a potential step change in quality assurance of FDM components, where the results can be applied to improved build path design and ensuring the inter-layer bond quality throughout the component.


372. A design strategy based on topology optimization techniques for an additive manufactured high performance engine piston

Saverio Giulio Barbieri, Matteo Giacopini, Valerio Mangeruga, Sara Mantovani

University of Modena e Reggio Emilia, Italy

In this paper, a methodology for a motorcycle piston design involving optimization techniques is presented. In particular, a design strategy is preliminary investigated aiming at replacing the standard aluminum piston, usually manufactured by forging or casting, with an alternative one made of steel and manufactured via an Additive Manufacturing process. In this methodology, the minimum mass of the component is considered as the objective function and the stiffness of important parts of the piston is employed as design constraint. The results demonstrate the general applicability of the methodology presented for obtaining the trusses layout

and thickness distribution of the structure.


10. Optimisation of Additive Manufactured Sand Printed Mould Material for Aluminium Castings

Philip Hackney, Richard Wooldridge

Northumbria University, United Kingdom

The foundry industry provides near net shape metal casting for a wide range of industries, producing components in ferrous and non-ferrous metals castings in a range of sizes from miniature to large castings such as zips to ships propellers. It has played a fundamental role in the development of man-kind and our current life styles from the Bronze and Iron Age are known for their ability to cast products and tools for example weapons and armour.

The sand casting process has little changed over the years, except for automation and mechanisation of the process, providing productivity advances, the fundamental process of sand compacted around a mould pattern, which is then removed to cast the metal has remained. For mass production this is economical and efficient however for development and prototyping the requirement for tooling and the production method design constraints means this stage often takes a long time and costly.

Additive manufacturing has been used to manufacture sand moulds for metal sand casting using laser sintering and sand bonding. This research focuses on optimisation of the build parameters for the Additive Manufacturing sand print bonded process developed by ExOne GmbhH Germany for Automotive Aluminium components.

The approach taken in this research is to evaluate characteristics of casting produced and relates to the permeability, dimensional accuracy, tensile and compressive crush strength, density, impact strength and high temperature resistance of the mould tool produced. These properties are required to compare the 3D Sand Printing (3DSP) process to Selective Laser Sand Sintering (DLSS) and traditional Furan based casting sand mixtures. The automotive turbo charger casing was used to validate the build parameters optimisation process.

This research would be of interest to designers and manufacturing engineers wishing to take advantage of the implications of having new design freedom, tool less manufacturing with short lead times in a wide range of materials using fundamentally tried and tested foundry industry casting technique. This research has demonstrated 3DSP process has the capability to manufacture sand patterns to permeability, accuracy, tensile and compressive strength comparable to traditional sand casting process.


385. Cost modelling and sensitivity analysis of wire and arc additive manufacturing

Chloe Rose Cunningham, Sondre Wikshåland, Fangda Xu, Alborz Shokrani, Vimal Dhokia, Stephen Newman

University of Bath, United Kingdom

With the proliferation and diversification of metal additive manufacturing (AM) processes in recent years, effective decision tools for process selection are of increasing importance. Wire and Arc Additive Manufacturing (WAAM) is an emergent metal AM technology with limited studies on the cost effectiveness compared to alternative manufacturing methods. This paper addresses this gap through the development of a novel time activity based cost model which, for the first time, includes post-processing activities. Modelling of the WAAM processing chain enables a sensitivity analysis to be carried out. A tool path based deposition cost is also introduced which accounts for geometric complexity and improves the accuracy of deposition time estimations. The results provide a comparison for two case study components that indicate WAAM has significant potential to be a cost effective manufacturing approach compared to electron beam, direct metal laser sintering and conventional CNC machining methods. Key cost drivers in WAAM have been shown to be indirect costs for both large and small components. However, smaller components are more influenced by direct costs and benefit from increases in parts per build plate. In contrast, shielding cost was highlighted as an area of particular impact for large components.

 
11:20am - 1:00pmSES 1.4: ICT-enabled technologies in Smart Factories
Session Chair: Paolo Pedrazzoli
Aula P (first floor) 
 

244. Structure approach to the design of automation systems through the IEC-61499 standard

Mauro Mazzolini, Franco Cavadini, Giuseppe Montalbano, Andrea Forni

Synesis Scarl, Italy

The main objectives of this study is the conception of an Engineering Support System (ESS) for sustainable optimization of automation tasks supervision, through a set of formalisms, methods and tools introduced to support the control engineer in the design phase of optimized supervisor solutions.

The ESS is based on the IEC 61499 standard for distributed automation, considered as technological reference for the development of automation logics for the new generation of manufacturing systems (CPS). It implements a new formalism for the control problem description and specification, guiding the control engineer within all the control design phases, in order to obtain high performance manufacturing systems while pursuing optimization of key parameter indicators, including for example minimal energy consumption and emissions. To such an aim it enables the possibility to formalize the control supervision problem into a constrained optimization problem to be solved with the most appropriate optimization algorithm selecting the most interesting optimization objective.

Finally, an innovative virtual commissioning platform is proposed. It allows to validate the developed automation tasks supervision system using the real targets running the control solution connected with the virtual model of the system to be controlled in place of the real one.


272. Development a modular factory with modular software components

Jay Jumyung Um, Klaus Fischer, Torsten Spieldenner, Dennis Kolberg

Technologie-Initiative SmartFactoryKL, Germany

Recent market trends require extremely short product life cycles to cope with individual customer requirements. The key technology to deal with these requirements is plug-and-produce which reduces engineering time to change the production lines rapidly. This challenge is solved by the concept of a modular factory which allows to reconfigure individual machine stations without the need of extensive engineering effort. Current solutions are focus on hardware approaches such as modular frames, cables and sensors. However software is still a barrier where the change of production line needs the reprogramming of individual devices. To deal with this challenge, the authors advocate the usage of the BEinCPPS architecture, which is built from open-source software components.


273. A microservice-based middleware for the digital factory

Michele Ciavotta, Marino Alge, Silvia Menato, Diego Rovere, Paolo Pedrazzoli

SUPSI-DTI, Switzerland

In recent years a considerable effort has been spent by research and industrial communities in the digitalization of production environments with the main objective of achieving a new automation paradigm, more flexible, responsive to changes and safe.

This paper presents the architecture and discusses the benefits of a distributed middleware prototype supporting a new generation of smart-factory-enabled applications with special attention paid to simulation tools.

Devised within the scope of MAYA EU project, the proposed platform aims at being the first solution capable to empower Cyber-Physical-Systems (CPSs) present at shop-floor level, providing an environment for their Digital Twin along the whole plant life-cycle. The platform implements a microservice-based, cloud-ready, hybrid IoT-Big Data architecture (i) supporting the distributed publication of multidisciplinary simulation models (ii) managing in an optimized way streams of data coming from the shop-floor for real-digital synchronization (iii) ensuring security and confidentiality of sensible data related to CPSs.


275. A review of the roles of Digital Twin in CPS-based production systems

Elisa Negri, Luca Fumagalli, Marco Macchi

Politecnico di Milano, Italy

The paper presents a through literature analysis of the Digital Twin concept, from the initial conceptualization in the aerospace, to the most recent interpretations in the Industry 4.0 manufacturing. Digital Twins provide virtual representations of systems along their lifecycle. Optimizations and decisions making would then rely on the same data that are updated in real-time with the physical system, through synchronization enabled by sensors. For this, a relevant role is covered by semantic metadata models. The paper discusses the new role of Digital Twins in manufacturing and avenues for future research.


377. Manufacturing System Upgrade with Wireless and Distributed Automation

Laura Grohn1, Samuli Metsälä1, Magnus Nyholm1, Lauri Saikko1, Eero Väänänen1, Kashif Gulzar1, Valeriy Vyatkin2

1Aalto University, Finland; 2Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, 97187, Luleå, Sweden

This paper presents a case study of developing a distributed factory automation system model upgrade with decentralized control deployed on a network of six programmable automation controllers communicating wirelessly. The goal is to develop a distributed system which is flexible enough, and easier to reconfigure with on-the-fly online software updates in a smart factory automation environment. Our approach benefits mainly production industries which require a robust and modular software design requiring less effort for their production line. The developed solution aims at flexibility, re-configurability, ease of maintenance and reduced downtime costs.

 
11:20am - 1:00pmSES 1.5: Robotics and Computer Integrated Manufacturing
Session Chair: Michele Gadaleta
Aula Q (first floor) 
 

95. How to Deploy a Wire with a Robotic Platform: Learning from Human Visual Demonstrations

Francesca Stival, Stefano Michieletto, Enrico Pagello

University of Padova, Italy

The advent of Industry 4.0 set a new standard in terms of workflow and customization. Agility is a key characteristic for industrial systems and the time needed for introducing a new article should be minimized. Production needs the flexibility to adapt to recurring changes and robotics is a major resource in obtaining this goal. In this paper, we address the problem of deploying a wire along a specific path selected by an unskilled user. An operator teach an arbitrary path by moving in a natural manner a tool deploying the wire through several pegs composing different possible routes. The system recorded the covered trajectories by using a camera network composed by both 2D and 3D cameras. The robot has to learn the selected path and pass a wire through the peg table by using the same tool. The work is part of a more complex project aiming at the development of a learning-based approach for robotized coils winding, to be used in the electric machines manufacturing industry. The configuration selected for our experiments is less demanding with respect to the real industrial environment in terms of movement precision. In fact, the focus of this work is related to correctness and wire deployment. The main contribution regards the hybrid use of Cartesian positions provided by a learning procedure and joint positions obtained by inverse kinematics and motion planning. Copper wire needs to be deployed along the path, some constraints are introduced to properly deal with this non-rigid material without breaks or knots. A learning framework based on Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR) is trained starting from an initial set of examples. Once a first model is ready, an incremental procedure let us introduce new examples starting only from mean, covariance and priors of the components forming the previous model. The projects has been selected for the European Robotics Challenges (EuRoC) and a benchmarking procedure has been created to test the system on a series of metrics validated by a super partes evaluation panel constituted by experts in robotics. Benchmarking tests regard mainly three aspects. The correct deploy of the wire is guarantee is no breaks or knots are present. The number of demonstrations necessary for following the correct peg sequence measures the generalization capability of the system. The time needed for updating the model gives a feedback in terms of learning adaptability. On top of these metrics, we take into account the time needed for computing the robot trajectory starting from the trajectory performed by the human demonstrator. All the parameters tested over performed the targets set during the analysis conducted by our industrial partner.


226. Autonomous Manufacturing of Composite Parts by a Multi-Robot System

Alfons Schuster, Michael Kupke, Lars Larsen

German Aerospace Center, Germany

Aerospace structures require a combination of low weight and high mechanical performance and thus often involve composite materials, e. g. carbon fiber reinforced plastics (CFRP) or fiber metal laminates (FML). The laminate structure involves complex layups, which makes manual production error prone. Today, there still is a lack of innovative production techniques to achieve competitive production rates. Automating this processes demands a smart and flexible, however robust system directly linked to the CAX-chain. We investigated a combination of cooperation industrial robots and computer vision without teaching of the robots.

Commercial products like Delmia or Process Simulate are useful for digital factory planning. Add-ons like Cenit’s Fast Suite extend the functionality towards digital production, but lack the ability of handling huge numbers of cut-pieces. It was shown in previous work that a robot’s target points for gripping and dropping cut-pieces can be derived automatically and subsequently the layup can be carried out autonomously. Also was shown that computer vision strongly improves process accuracy and robustness. The focus of this paper lies on the practical implementation of a smart manufacturing execution system in a multi-robot environment. Major components of the cyber-physical system are the Manufacturing Execution System (MES), the robots and their controllers, one ore multiple computer vison systems for detection of the goods being handled, and a simulation environment called CoCo for collision avoidance.

This work considers pick-and-place processes, which consist of the steps picking, transfer, dropping and post-drop treatment. Our scenario was an airplane skin demonstrator made of dry CFRP sheets. The jig for placing the cut-pieces is half-shell shaped with a diameter of approx. 4 m and a length of approx. 2 m, while the 108 cut-pieces are approx. 1.2 m by 1.8 m and approx. 1.2 m by 0.8 m in size and are provided in a drawer based storage system. For determining where to grip we use one computer-vision system mounted to a KUKA Quantec KR210 R3100 robot. A second, identical robot with identical grippers is operated using the image coordinates of the same camera. Both robots are mounted to one linear axis of 8 m length. The information on which cut-piece to grip, where to grip it from, what is it’s contour and where to exactly move the grippers for gripping and dropping is contained in a proprietary Job Definition File format (jdf), which can be considered a preliminary step to later extensions of the CPS by a production planning and execution agent. A parser converts the generic jdf-information to an action list for each robot comprising setting the tool center point, move the robot, switch the grippers and do the post-drop tacking. The robots receive their actions by the KUKA technology package Ethernet KRL. Time critical movements, like cooperative cut-piece transfer with two robots, are first parametrized and then executed synchronously by the KUKA technology package RoboTeam. Thus, the fully automated, autonomous production of a generic airplane part with multiple robots in a complex environment could be demonstrated.


44. Offline CAD-based robot programming and welding parametrization of a flexible and adaptive robotic cell using enriched CAD/CAM system for shipbuilding

Lucía Alonso Ferreira, Yago Luis Lapido Figueira, Isidro Roberto Fernández Iglesias, Manuel Álvarez Souto

AIMEN Technology Center, Spain

Shipbuilding is usually a handwork process, many shipyard’s facilities are poorly optimized and they haven’t flexibility enough for more complex manufacturing. In 2015, shipbuilding sector emerged with the purpose of dynamizing its R&D environment, developing of advanced manufacturing technologies that make easier the technological evolution of the sector.

The purpose solution is a hyper-flexible welding robotic cell, composed by a gantry of three axes with a six-axes robot assembled. The nine axis are fully coordinated by the robot controller. The dimensions of the three-axes are 5x4x2.5 m, the anthropomorphic robot is a KUKA KR16-2 model. The system is provided with a localization system based on machine vision.

The main topic of this development is the software that help to program this robotic cell in a CAD environment allowing implement welding sequences to an inexperienced programmer: ‘Offline automatic system programming’.

The worker, through the CAD program, is capable of configure the welding parameters and program the robot in an automatic way, generating the robot trajectories module and is responsible for sending it automatically to robotic system, without using the console.

The machine vision locates the part to be welded. This cell has two cameras embarked on the gantry that scan the work space; the software combines multiple images with overlapping fields of view, producing a high-resolution image, locates the part into the created one and calculates its pose – position and orientation –, which is sent to the robot.

The app is embedded in the open source software FreeCAD, in order to make it accessible for Small and Medium-Sized Enterprises. In this program, a workbench was created using Python language. The user selects in the CAD model the joint that wants to weld and, through the interface, the user adds welding parameter’s –e.g. voltage, current, gap…– and location parameters –eg. the workobject or the distance between points-. The welding joint 3D points are extracted from the CAD and the pose of the part to be welded is result from machine vision system. All the data are stored in a configuration file in a XML format. Therefore, this file associates CAD data with process parameters, getting an enriched CAD/CAM file.

With all the data parameterized, the necessary calculations are made to determinate the point coordinates of each joint, and generate a DAT file -KUKA file format that stored the path points-, that is sent to robot. The calculation of the trajectory takes into account the coordinated movement of the nine axes.

All the process instructions are sent to the robot controller from the workbench created on FreeCAD. This is carried through a communication between the robot and the application developed, based on sending and receiving a XML structure.

With this system, manually programmed paths are eliminated by automatic generation off-line with CAD systems. This system is adapted to small batch manufacturing with different parts designs; the system is ‘easy work’ so that inexperienced personnel can use it. In addition, this adaptive cell is more productive than a conventional robotic system.


296. Semantic modelling of hybrid controllers for robotic cells

Mathias Haage1, Jacek Malec1, Anders Nilsson2, Maj Stenmark1, Elin Anna Topp1

1Lund University, Sweden; 2Department of Automatic Control, Lund University, Box 118, 221 00 Lund, Sweden

Programmable Logic Controllers (PLCs) play an important role in integration of hardware and software in industrial robot cells featuring an increasing amount of heterogenous equipment from several vendors. PLCs are also particularly useful for implementing hybrid controllers for the cells. PLCs are defined in the IEC 61131 standard including several programming languages as defined in the 61131-3 part of the standard. In this paper we propose a semantic grounding of the Sequential Function Charts (SFC) notation for specification of PLC programs. Semantic modelling of PLCs allows the use of automatic reasoning methods to accelerate cell setup and (re)configuration, including generation of SFC descriptions. Our semantic grounding is expressed in the OWL semantic language and forms part of our semantic robot framework, called KIF (short for Knowledge Integration Framework). KIF is a set of ontologies and associated tools to ensure interoperability between heterogenous equipment making up a robot cell. We also present a tool set for manipulating SFC instances stored in RDF triple stores reachable through the RDF4J framework. SFC instances may be stored declaratively, analysed, modified (including various forms of composition) and exported into the run-time system for execution. For this last purpose we use the JGrafchart tool. The semantic grounding and tool set are evaluated in a teaching-by-demonstration experiment in a small parts assembly setup featuring a collaborative industral robot, ABB YuMi, where the tool set is used to create and execute SFC descriptions on-the-fly based on data from human demonstrations.


36. A New Model of Modular Automation Programming in Changeable Manufacturing Systems

Tarek Al-Geddawy

University of Minnesota Duluth, United States of America

Manufacturing systems in Industry 4.0 are changeable, smart, connected and more autonomous. The structure of a changeable manufacturing system allows for physical reconfiguration, however, reprogramming controllers has been always performed manually for each new system configuration. The presented model combines different ladder logic codes corresponding to different system configurations, modularizes them and produces smaller pieces of code, which automatically get merged and downloaded to the different system controllers. The model uses Cladistics and Design Structure Matrix (DSM) to prepare the modular codes. A case study of a changeable robotic assembly system is presented.

 
11:20am - 1:00pmSES 1.6: Manufacturing Process and Technology
Session Chair: George-Christopher Vosniakos
Aula R (first floor) 
 

49. Minimizing the springback effect in dual-phase steel parts by Finite Elements Method

Tiago Resende Gomes, Francisco J. G. Silva, Raul D. S. G. Campilho

Azevedos Indústria SA, Portugal

Developments in the automotive industry, has been over the years increased in order to increase safety and comfort, and reduce the weight of automobiles. These conditions imply the use of materials with high strength, but at the same time be lighter.

The use of Dual-Phase steels in this field, allows not only get the required conditions, as well as be more competitive, since most of the current industries using "soft" steels, more easily formable. However, taking into account the characteristics of these materials is their rather complicated stamping process, especially with regard to springback.

This work was done in order to better learn these steels and their production process through simulation software that predicts the results of stamping and minimize problems resulting from this process.

It was verified that the use of simulation software, allowed anticipate and reduce the problems associated with springback, and thus facilitate the perception and monitoring of these steels. Consequently, it was confirmed that the realization of simulation of parts and respective compensation tools can reduce time and costs in the preparation of tools.


52. Selection of Force Creation Method for Press Forming Machinery

Jarno Tolvanen, Ville Leminen, Panu Tanninen, Juha Varis, Sami Matthews

Lappeenranta University of Technology, Finland

Environmental aspects have become increasingly important in today's business. In packaging industry this has created an increased demand for fibre-based packaging solutions which present a renewable and environmentally friendly alternative for oil based materials. One of such materials is paperboard, and for example trays made of paperboard can be an alternative for traditionally used plastic trays in food packaging. Nowadays there is a need for cost-effective small scale machinery. In this study the objective was to define the best method to produce the force needed in the compact paperboard tray pressing machine. The machine has to match the demanding requirements about force production, accuracy and also hygienic requirements.

Two different force creation methods were studied in this article using Score Table -analysis and SWOT-analysis.

Results indicate that the electric actuator system had several key features compared to the hydraulic system that gave it a clear advantage, including high force production, accuracy and cost efficiency.


15. A cross wedge rolling process for forming 70 mm diameter balls from heads of scrap railway rails

Zbigniew Pater, Janusz Tomczak, Tomasz Bulzak

Lublin University of Technology, Poland

The paper describes an innovative technique for producing balls which are used as grinding media in ball mills. With this method, balls are formed from heads of scrap railway rails. The proposed two-stage technique is based on cross wedge rolling. First, a rail head is formed into a cylindrical bar with a diameter of 52 mm. Next, the bar is formed into four balls, each with a diameter of 70 mm. Given the two-stage design of the process, an innovative flat-wedge reversing mill had to be designed. The paper presents the design of such a mill. In addition, it also reports the numerical findings and experimental results of producing balls by the proposed technique.


290. Hybrid Cooling and Lubricating Technology for CNC Milling of Inconel 718 Nickel Alloy

Alborz Shokrani, Vimal Dhokia, Stephen T Newman

University of Bath, United Kingdom

High material strength, creep and corrosion resistance have made nickel based alloys an attractive material for aerospace, gas turbine and marine industries. It is reported that approximately 80% of the super alloys used in aerospace industries are nickel based alloys. This accounts for over 50 wt.% of materials used in an aero engine. Inconel 718 is the most widely used alloy of nickel and forms 35% of annual volume production of nickel alloys. Due to the high material strength and work hardening tendency of Inconel 718, high temperatures and forces are produced during cutting operations. Low thermal conductivity of the material prevents effective heat dissipation resulting in very high temperatures at the cutting zone. These high temperatures together with high cutting forces can lead to significantly reduced tool life and poor surface quality of machined parts. The surface quality is particularly important as it affect the service life and performance of the machined parts mostly used in aero engines and gas turbines. As a result, machining components made from nickel based alloys is usually associated with low cutting speeds, low productivity and high machining costs. There are a limited number of studies, predominantly on turning operations that have stated that cryogenic cooling is an effective technique for reducing the cutting temperature and as a result improving the surface integrity and allowing for higher cutting speeds to be used. This paper presents one of the very first studies on the effects of hybrid cryogenic cooling combining liquid nitrogen coolant and vegetable oil lubricant on the machinability of Inconel 718 in CNC milling. A series of experimental investigations are conducted under different cutting environments, namely cryogenic and conventional dry and emulsion. Chip morphology and surface integrity of the machined parts is then studied and statistically analysed. The analysed results are then presented in order to identify the effects of cryogenic cooling in CNC milling as compared with conventional flood cooling.

 
1:00pm - 1:50pmLunch break
Courtyard at ground floor 
1:50pm - 3:10pmSES 2.1: Collaborative Robotics in Smart Manufacturing
Session Chair: Pedro Neto
Aula Convegni (first floor) 
 

73. Skill based dynamic task allocation in Human-Robot-Cooperation with the example of welding application

Aaron Geenen, Rainer Müller, Matthias Vette

ZeMA Zentrum für Mechatronik und Autom. gemeinnützige GmbH, Germany

Due to technological and organizational boundary conditions the automation of assembly processes is usually difficult to solve. It is subject to technological challenges and economical risks due to high numbers of variants of parts as well as the complexity of the assembly processes to be managed reliably. Experience has shown that full automation of production cycles is often inefficient.

For an implementation of efficient automation, it is necessary to develop flexible and adaptable production systems that can be applied to a skill-based dynamic task allocation. This ensures high efficiency of the production plants.

As part of the research projects TRSE (semi-automated robot welding for single item production) and 4by3 (Modularity, Safety, Usability, Efficiency by Human-robot-collaboration), at ZeMA seeks to develop new process technologies, planning tools, and adequate equipment in order to enable efficient and customizable automation for various production processes.

Human-robot-cooperation (HRC) is an approach of flexible automation with a skill based dynamic task allocation. Employee and robot work together without a separating protection device in an overlapping work space. The idea is to support the operator in the production process with a HRC robot system to achieve higher process efficiency and to improve quality.

One solution for a flexible skill-based automation of chosen processes is represented in Human-robot-cooperation for assembly of high quality machines for the medical industry. Instead of an unflexible fully automated approach, a semi-automated one is being developed, that can be easily controlled by the operator on the shopfloor. Therefore know-how gained from manual processes will be efficiently transferred into the assembly system.


64. Method for design of human-industrial robot collaboration workstations

Fredrik Ore1,2, Lars Hansson2,3,4, Magnus Wiktorsson1

1Mälardalen University, Sweden; 2Scania CV AB, Global Industrial Development, Södertälje, Sweden; 3University of Skövde, School of Engineering Science, Skövde, Sweden; 4Chalmers University of Technology, Department of Product and Production Development, Gothenburg, Sweden

Human Industrial robot collaboration (HIRC) is a rapidly growing field in research. Personal safety in a fenceless system and novel communication between human and industrial robot are two of the areas under research. The overall vision of the HIRC systems are to combine the strength, endurance and accuracy of the industrial robot with the intelligence, flexibility and tactile senses of the human to create more productive production systems with lower ergonomic loads on the operator. There already exists a number of collaborative robots on the market that is designed to stop at an unforeseen impact, thus work safe beside a human in a fenceless environment. However, these robots are typically weak and slow variants of industrial robots. Even though collaborative robots exist on the market, the possibility to virtually evaluate the entire system of robot and human collaboration, before making an investment decision, is very limited in available simulation software Even less information about methods for using simulation tools in HIRC analysis is available. In order to meet this need, a demonstrator simulation software were developed, making it possible to design and evaluate HIRC system layouts. The aim with this paper is to present a HIRC design method that put this novel demonstrator software’s possibilities in the overall production system design process. This method could be used in design decisions early in the production development process.

An industrial HIRC design case was used to identify the needs and demonstrate the use of the method. The developed HIRC design method is divided to three areas, resource allocation, simulation and evaluation of design alternatives and mathematical optimisation to achieve optimal solutions. Resource and task allocation is a challenging issue where multiple objectives have to be considered to reach the most beneficial solution. The presented method include considerations of automation constraints to limit the possible task allocations. The next area is simulation and evaluation of production designs. The simulation is based on 3D CAD data and includes design of multiple production layouts based on the geometric layout. The simulations produce quantitative outputs considering time, biomechanical load and production cost. These outputs are considered when the production system layout and the exact task allocation between human and robot are decided. Mathematical optimisation algorithms can also be used in order to find the optimal solution based on system objectives and constraints. The optimal solution to a particular production system design problem is found in the entire spectrum from a fully manual solution, a HIRC solution, to a fully automated robotic station. The presented method show how the developed demonstrator software can be used in a systematic way to enable design of productive and sustainable HIRC workstations.


283. Portable rapid visual workflow simulation tool for human robot coproduction

Radoslaw Dukalski1, Argun Cencen1, Doris Aschenbrenner2, Jouke Verlinden1

1Delft University of Technology, Netherlands, The; 2Zentrum für Telematik e.V., Magdalene-Schoch-Str. 5, D-97074 Würzburg, Germany

Within the European Factory-in-a-day project, the aim is to improve communication between automation integrator and factory owner, in their analysis of feasibility and appropriateness of automating a manual task. A visualisation tool with preconfigured workflows and working principles, with specific focus on efficient human-robot coproduction workflows can improve this process. This paper describes the Workflow Simulation Tool, which is part of the Human-Robot Coproduction Methodology, currently in development. The tool encompasses a portable tablet PC, which runs a visual modelling environment combined with a handheld 3D scanning solution. The tool also features pre-modelled template layouts, implementation of a checklist of persistent notes and portable visual documentation. The tool’s appropriateness was iteratively validated in collaboration with automation integrators. This evaluation showed that offering an interactive visual simulation enriches the dialogue during conceptual design and helps in revealing requirements that otherwise only appear during or after implementation.


224. Development of a dual-projected-based automated interference matrix algorithm for Industry 4.0

Wang Chi-hsin1, Cheng Chen-Yang2

1Tunghai University, Taiwan; 2National Taipei University of Technology (Taipei Tech), Taiwan

In order to perform to Industry 4.0 standards, enterprises are moving forward with automatic factory and intelligent manufacturing. However, there are concerns pertaining to the use of automation for assembly sequence planning (ASP). This is a matter of great importance, as traditional product assembly incurs considerable manpower and time, generally accounting for 20–70% of the total manufacturing workload. At present, a number of systems are available that automatically generate an assembly sequence through a matrix representing the collide relationship between the components—i.e., an interference matrix. Yet, it is by no means easy to automatically define and build this kind of matrix. In this paper, we develop a dual-projected-based automated interference matrix (DPIM) algorithm that analyzes the relations between the components of a given product. In order to reduce the number of times that collide detection is performed in comparison with the method only do collision detection, the DPIM algorithm relies on static interference detection and dual-projected detection to generate a contact matrix, a direction contact matrix, and an interference matrix. By reducing the number of times collide detection is performed, DPIM can reduce the workload of assembly, thereby reducing the total manufacturing load overall and the manufacturing time likewise.

 
1:50pm - 3:10pmSES 2.2: Smart Factories and Industrial IoT
Session Chair: Michele Ciavotta
Aula N (first floor) 
 

232. Internet-of-Things paradigm in food supply chains control and management

Riccardo Accorsi1, Marco Bortolini1, Giulia Baruffaldi2, Francesco Pilati1, Emilio Ferrari1

1University of Bologna, Italy; 2Department of Management and Engineering, Padova University, Stradella San Nicola, 3 – 36100 Vicenza (Italy)

Starting from the definition of the Internet-of-Things (IoT) paradigm, the aim of this paper is to discuss goals and expected strategies for the design and building of a IoT architecture aiding the planning, management and control of the Food Supply Chain (FSC) operations. A comprehensive architecture of the entities, the physical-objects, the physical and informative flows, the stages and the processes to be sensed, tracked, controlled and interconnected is given to illustrate the interdependencies between the observed supply chain and the exogenous environment in terms of physical and information inputs, outputs and mutual impacts. A simulation gaming tool embedding and implementing the IoT paradigm for the FSC management is also proposed and illustrated to showcase the potential benefits and opportunities for more direct integration of the physical food ecosystems into virtual computer-aided control systems.


219. A Wireless Intelligent Network for Industrial Control

Mohammad Gholami, Mohammed Salem Taboun, Robert Brennan

University of Calgary, Canada

This paper reports on an ad hoc wireless sensor network architecture for industrial sensing and control applications. This approach is tested using a large-scale (400-676 node) agent-based simulation of a factory environment that is subject to noise and blockage. The basic problem tackled by the distributed system is mobile node tracking. To support this work, we introduce two classes of metrics: (1) a set of tracking perfor-mance metrics, and (2) a set of network architecture efficiency metrics. The results of our experiments show that the proposed distributed system adapts readily to changes in the sensing environment, but this higher level of adaptability is at the cost of overall efficiency.


43. Enabling Connectivity of Cyber Physical Production Systems: A Conceptual Framework

Rafael A. Rojas C.1, Erwin Rauch1, Renato Vidoni1, Dominik T. Matt1,2

1Free University of Bolzano, Italy; 2Fraunhofer Italia Research s.c.a.r.l., Innovation Engineering Center (IEC), via Macello 57, Bolzano, 39100 Italy

In the Fourth Industrial Revolution, the Internet of Things will allow integrating all instances of the value chain of products, enabling communication and cooperation between them. This requires a high level of integration and interoperability of a wide spectrum of communication technologies in all layers of a network system. Inside a Smart Factory, the same problem takes a more concise form, and Cyber-Physical Systems (CPS) such as humans, robots, smart machines, products and sensors, have to be synchronized one with another and with the external world to share information and trigger actions to make possible both flexibility and high level of customization, which characterizes the Industry 4.0 revolution. Moreover, all data generated at the Smart Factory should be collected, stored, and shared to further Big Data Analysis and decision making. This must combine machine-to-machine communication, machine-human interaction and the Internet. In this work, the conceptual development of such a network to implement a Smart Factory at the Mini-Factory Laboratory of the Free University of Bolzano is presented. The objective is to set up an Industrial Internet System (IIS), first by homogenizing and integrating the communication systems of the end-nodes of the Mini-Factory, i.e., sensors, robots, etc., through the necessary hardware and middle-ware, and second, by constructing a centralized backbone network where all valuable information is collected for further data analysis. This will make possible the implementation of an application layer oriented to Industrial Internet of Things, and the decentralization of decision making allowed by the cyber-physical

capabilities together with a centralized high-level optimization interface.


337. Process monitoring technology based on virtual machining

Eun-Young Heo2, Hikoan Lee2, Cheol-Soo Lee3, Dong-Won Kim1, Dong Yoon Lee4

1Chonbuk National University, Korea, Republic of (South Korea); 2CAMTIC, Jeonju-si, Jeollabuk-do, 54852, Korea; 3Sogang University, Seoul, 04107, Korea; 4Korea Institute of Industrial Technology, Ansan-si, Gyeonggi-do, 15588, Korea

This paper presents a process monitoring system which is integrated with virtual machining for a more accurate diagnosis of machining operation without the need for test machining. Virtual machining simulates the material removal process along the NC tool path and predicts the static and dynamic characteristics of the operation. The status data of a machine tool from the CNC and sensor signals are integrated with pre-estimated virtual machining data. The proposed monitoring system analyzes the integrated data to diagnose the machining operation in (near) real-time. The application of the monitoring system to 3 axis machining is demonstrated with experimental results.

 
1:50pm - 3:10pmSES 2.3: Manufacturing Operations, Supply Chain and Logistics
Session Chair: Cristovao Silva
Aula O (first floor) 
 

50. Applying Looks-Like Analysis and Bass Diffusion Model Techniques to Forecast a Neurostimulator Device with No Historical Data

Farnaz Ganjeizadeh, Howard Lei, Preetpal Goraya, Erik Olivar

CSUeastbay.edu, United States of America

This work utilizes looks-like analysis and the Bass diffusion model to generate sales forecasts of a responsive neurostimulation (RNS) system. Due to the lack of historical data, a combination of techniques is utilized to predict the device’s demand. Looks-like analysis is used to analyse analogous devices and their sales patterns to select the device closest to the RNS system. Next, parameters for the Bass diffusion model are estimated, and potential baseline forecasts are developed using two methods. Results suggest that peak sales for the device will occur around years 2021-2024.


9. Assessment of air cargo airlines: An interpretive structural modeling approach

Aman Gupta, Robert Walton

Embry-Riddle Aeronautical University, United States of America

All-cargo airlines carry about 50% of the global airfreight, with most of the rest carried as belly freight on passenger aircraft. There are many financial models designed to predict the financial health of a firm, but they do not assess many nonstatistical factors that may influence the models. Using Interpretive Structural Modeling (ISM) methodology this study will explore the nonstatistical factors that might affect a firm. ISM allows a better understanding of the mutual influence among different attributes and the consequences which helps the decision maker make more informed decisions. The researcher will be using ISM methodology to summarize and identify the relationships among attributes that impact the competitive advantage of a cargo airline, operational factors that might influence the firm’s processes and characteristics that might affect the overall financial stability of the airline. Relationships among attributes will be derived and structured into a hierarchy in order to derive subsystems of interdependent elements with corresponding driving power and dependency.


7. Improving Road Transport Operations using Lean Thinking

Jose Arturo Garza-Reyes1, Juan Sebastian Beltran Forero2, Vikas Kumar3, Bernardo Villarreal4, Miguel Gaston Cedillo-Campos5, Luis Rocha-Lona6

1University of Derby, United Kingdom; 2Warwick Manufacturing Group, The University of Warwick, Coventry, CV4 7AL, UK; 3Bristol Business School, University of the West of England, Bristol, BS16 1QY, UK; 4Departamento de Ingenieria, Universidad de Monterrey, San Pedro Garza Garcia, 66238, México; 5National Laboratory for Transportation Systems and Logistics, Mexican Institute of Transportation, Querétaro, 76703, México; 6Instituto Politécnico Nacional, ESCA Santo Tomás, Mexico City, 11340, México

Purpose – Despite the large number of successful examples of companies that have implemented lean thinking in their processes, it is still challenging to find organisations which have adopted lean thinking in their transport operations. The main reason is because transport operations have been considered as a wasteful activity in the literature during the last decades, and hence managers do not spend time and resources in wasteful activities. Nevertheless, the importance of transport operations has nowadays been widely recognised in a variety of industrial sectors and to support the economic development of nations. However, few investigations have applied lean thinking in transport operations as a potential improvement strategy. The aim of this research is therefore to document a case study where the transport operations of one of the leading providers of paper-based packaging solutions in the world, based in Bogota, Colombia, were identified, measured and improved using lean concepts, methods and tools.

Design/methodology/approach – The research is considered an exploratory and analytical case study that took place in the transport process of one of the leading providers of paper-based packaging solutions in the world located in Bogota, Colombia. The study measured and analysed the performance of the transport operations using lean tools and techniques with the purpose of finding improvement opportunities. The methodology of the research was divided into 4 steps: (1) direct observations of the entire transport operation; (2) collection and analysis of the data; (3) creation of a Transportation Value Stream Mapping (TVSM) of the process, (4) measurement of the Transportation Overall Vehicle Effectiveness (TOVE); and (5) proposal of recommendations and possible solutions to improve the process.

Findings – The TVSM identified six wastes in the transport operations of the case organisation, namely: waiting, resource utilisation, excess movement, over-production, over-processing and behavioural. On the other hand, with the development of twelve indicators, the TOVE measure resulted in an efficiency of 54%. Thus, the study identified and proposed improvement opportunities based on the results of the TVSM and TOVE.

Research limitations – Lean thinking is a powerful philosophy that needs time for its development and full adoption in any process. Thus, the research took five direct observations that described how the process works, however, the study can be more accurate with more data information and more time to develop the techniques. Nevertheless, the case company recognised the positive impacts of the research and it can hence continue the project with more detail.

Practical implications – This study is one of the few investigations which have explored the use of lean thinking with the purpose of improving transport operations. Thus, it has positive impacts for subsequent studies within the field. In addition, this research provided strong tools and techniques to the case organisation in order to increase and improve the performance of its transport operations. Managers can apply the concepts developed in the research and create a culture of continuous improvement in this area.

 
1:50pm - 3:10pmSES 2.4: Lean and Agile Manufacturing
Session Chair: F. Frank Chen
Aula P (first floor) 
 

27. Efficiency assessment of Reconfigurable Manufacturing Systems

Ignacio Eguia Salinas, Gabriel Villa, Sebastián Lozano

FIDETIA - University of Seville, Spain

Reconfigurable Manufacturing Systems (RMS) are advanced production systems designed for rapid change in its configuration, allowing it to adapt its production capacity and functionality to the dynamic changes of the demand of the part types. As with any other manufacturing system, the efficiency of RMS should also be assessed. In this paper, a novel Data Envelopment Analysis (DEA) approach is proposed to assess the technical efficiency of RMS by benchmarking the observed time allocation of the different system configurations and the inputs consumed and output produced in each of them. The inputs considered are the time usage of the different RMS modules, labour and energy consumed. The outputs are the number of units produced of each part type. The production possibility set is determined by previous observations, from which the best practices are identified. The proposed approach is illustrated on a simulated dataset.


91. Capability matchmaking procedure to support rapid configuration and re-configuration of production systems

Eeva Maria Järvenpää, Niko Siltala, Otto Hylli, Minna Lanz

Tampere University of Technology, Finland

Rapid responsiveness in terms of processing functions, production capacity and order dispatching is required from today’s production systems. This paper introduces a capability-based matchmaking procedure, which supports rapid configuration and re-configuration of production systems. The approach relies on formal OWL-based descriptions of both product requirements and resource capabilities. The base algorithm for the matchmaking is introduced together with the required rules for combined capability calculation and capability matchmaking. The presented approach supports the system designer and reconfiguration planner by automatically suggesting possible resource alternatives for certain product requirements.


326. The development of simulation model for self-reconfigurable manufacturing system considering sustainability factors

Sang il Lee1, Kwangyeol Ryu1, Moonsoo Shin2

1Pusan National University, Korea, Republic of (South Korea); 2Department of Industrial and Management Engineering, Hanbat National University, 125, Dongseo-daero, Yuseong-gu, Daejeon, 34158, South Korea

Currently, there are many research about sustainable and eco-friendly manufacturing system. However, up to now, there are not many studies yet discussing about the integration between sustainability and self-reconfigurability. In this paper, the relationship between self-reconfigurability and sustainability is investigated, especially when a manufacturing system changes its process based on its new-determined goal. This paper also provides an experiment result by using simulation model consider a process reconfiguration and sustainability factors. Through existing research results, the literature is reviewed in order to obtain the relationship between self-reconfigurability and sustainability. The appropriate sustainability factors for self-reconfigurability such as energy efficiency, resource efficiency, and so on, has been checked and selected by using AHP(Analytic hierarchy process). Then, the simulation model will be developed by considering the selected sustainability factors. To check and analyze how sustainability factors affect manufacturing processes and how sustainability factors, also change when manufacturing process are changed. The result of this paper can be a basis for the future research to increase sustainability in a self-reconfigurable manufacturing system..


357. Towards practical guidelines for conversion from a fixed to a reconfigurable manufacturing automation system

Alan Coppini1,2, Michael Saliba2

1Trelleborg Sealing Solutions Malta, Malta; 2University of Malta, Msida MSD 2080, Malta

It is generally considered to be a key requirement in the development of reconfigurable manufacturing systems, that economic feasibility is only attainable if the system is defined to be reconfigurable at the outset of its design. In this work we consider the potential exception to this requirement, in the context of a common industrial scenario where a specialized and expensive manufacturing machine or system will otherwise be rendered useless due to loss of business of the particular product being manufactured. Specific guidelines to convert from a fixed to a reconfigurable system are proposed, and evaluated through a case study.

 
1:50pm - 3:10pmSES 2.5: Digital Product and Process Development
Session Chair: Francisco J. G. Silva
Aula Q (first floor) 
 

299. Design procedure to develop dashboards aimed at improving the performance of productive equipment and processes

Sandrina Vilarinho, Isabel Lopes, Sérgio Sousa

University of Minho, Portugal

Technological evolution and constant changes in customers’ and other stakeholders’ requirements challenge the organizations to keep up with those changes and at the same time maintain high levels of quality. Considering those requirements, the kaizen approach, more specifically the TPM methodology and its pillar kobetsu kaizen, and the visual management, are key elements to ensure organizations’ response to this challenge. The dashboard is a potential visual management tool that presents key information in order to achieve the objectives defined by organizations. In this way it allows the users to identify, explore and communicate problematic areas that need intervention and to improve decision making.

Even though we find in the literature information about the implementation of dashboards in companies, there is visibly a gap concerning methodologies to develop dashboards oriented to continuous improvement at the shop floor level. This paper intended to fill this gap, having as main objective the development of a performance improvement support methodology to the processes and production equipment, based on the development and implementation of a dashboard.

The work was developed in the context of a pilot company, with the involvement of the employees associated with the production areas. The development of the methodology was based on: the diagnosis of the pilot company; requirements survey; development of a dashboard model and the computer system to support its deployment; development and implementation of procedures and resources needed for the implementation. As a result, it was found that the steps followed were effective against the support methodology objectives. So, a generalization of the developed methodology was realized in order to be a guidance to other companies that want to improve the performance of their processes and productive equipment.

The paper provides useful information regarding the application of dashboards on operational level to improve performance management and decision making. It also explores the challenges in implementing this visual management tool from a practical perspective.


366. A generic decision support tool to planning and assignment problems: Industrial application & Industry 4.0

Nathalie Klement1, Cristovao Silva2, Olivier Gibaru1

1ENSAM, France; 2CEMUC, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, 3030-788, Coimbra, Portugal

Decision support tools are essential to help the management of industrial systems at different levels: strategic to size the system; tactical to plan activities or assign resources; operational to schedule activities. We present a generic and modular decision support tool to solve different problems of planning, assignment, scheduling or lot-sizing. Our tool uses a hybridization between a metaheuristic and a list algorithm. The specification of the considered problem is built into the algorithm list. Several tactical and operational problems have been solved with our tool: a problem of planning activities with resources assignment for hospital systems, a lot-sizing and scheduling problem taking into account the setup time for plastic injection. The scheduling problem with precedence constraints is being solved. At the strategic level, this tool can also be used as part of the Industry 4.0 to design reconfigurable production systems. This paper summarizes the already solved problems with the proposed tool, and presents the

evolution of our tool.


288. Engineering Change Management Data analysis from the perspective of Information Quality

Lauri Tapio Jokinen, Ville Vainio, Antti Pulkkinen

Tampere University of Technology, Finland

Advanced manufacturing companies process a large number of Engineering Change Requests (ECRs) every year. Having a steady flow of ECRs and an efficient change management process is vital to companies in order to continuously improve their products from perspectives of different stakeholders. The processing times for ECRs vary, among other factors, due to quality of the requests. While a small number of requests gets processed in less than a day, for some the processing may take up to one year. The long processing times lead to unnecessary delays to the requested improvements that would, for example, bring added value to customers or decrease manufacturing costs of products.

This paper is based on the thorough analysis of two thousand Engineering Change Objects and a number of semi-structured interviews conducted in a case company. The case company has sales, engineering, manufacturing and service operations that are globally distributed in different sites and offices. The company processes more than a thousand ECRs yearly, and the number has been increasing significantly during the last decade. The goal of the research was to find out reasons for the varying ECR processing times by classifying Engineering Change Objects and by searching for similarities, differences and reoccurring patterns within the ECR data.

The analyses show that while it is possible to find patterns and create guidelines related to information quality, in many cases analyzing data afterwards is difficult due to part of the Engineering Change modification history disappearing during the process. The final form of a change request is usually of an adequate quality to the handler, even if the initial request was missing several key elements. However, while the primary handler of the ECR often needs only a certain amount of information, ECRs should include more than the minimum in order to be comprehended also by other stakeholders who use the data. Also, it is not enough that the ECR is comprehensible to current handlers; it also needs to remain usable in the future.


267. Proposal for the representation of mechanical and motion control schematics, MMCS

Julio Garrido Campos, David Santos Esterán

Vigo University, Spain

Manufacturing machines design is a process that combines knowledge of different areas. Many modern machines use motion control systems –inverters, servo-drives, synchronous motors, encoders, etc.-, and the interaction and interdependence between mechanics and electronic control is very high. In modern machinery this complexity increases with the possibility of defining temporal and electronic kinematic relations between axes–as for instance master-slave relationships, CAM table dependencies, etc.–, as well as the use of virtual axes associated with real axes for control reasons.

During the machine conceptual and detailed design, the mechanical elements and components representation come naturally, but not so their relationship with control devices which drive them. On the other hand, control programs and algorithms uses very simplistic representations of the mechanics; just as black boxes. Mechanics, electronics and control have their own widely used standards and design methodologies. However, they are oriented to their particular scopes, and hence to their elements and relations representation strategies. They hardly provide the possibility of providing or including relevant information from another field.

A review of the different standards used in graphic engineering from the mechanical and the control field (ISO128, Technical Drawings, ISO 3952-1: 1981 Kinematic diagrams - Graphical symbols, ISO 369: 2009, PLC-Open for motion, IEC 61131, STEP UMRM, etc.) brings the conclusion that there is no adequate representation methodology to cover, for the new modern machines requirements, mechanical and control design views at the same time. This article develops a new designing information model for this situation. This new systems representation method is a combination of the main standards used in the design of machinery, but taking into account only those common and relevant information for all technology views-mechanical and control- obviating what would be considered irrelevant for the rest.

This new model, in its digital representation, can help achieve some of the objectives of an industry 4.0 implementation: “a model of the ‘smart’ factory of the future where computer-driven systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions based on self-organization mechanisms”(1). Or more specifically, this virtualization is defined as a virtual copy of the Smart Factory created by linking sensor data with virtual plant models and simulation models (2).

The model presented in this paper will be worth for the design process of complex machines. The use a “graphic” version of the model would bring profits in the communication and understanding between mechanical designers and control designers. And an “digital” information model would become in the link between the "software model" and the "mechanical model" of the virtualized machine/factory.

The article presents the foundations of this new modeling information system and methodology and some case use examples.

[1] Ron Davies. Industry 4.0: Digitalisation for productivity and growth. EPRS | European Parliamentary Research Service.

[2] European Parlament. Directorate general for internal policies. Policy department: Economic and scientific Policy. Industry 4.0, 2016 (ISBN: 978-92-823-8815-0).

 
1:50pm - 3:10pmSES 2.6: Reliability and Predictive Maintenance
Session Chair: Munir Ahmad
Aula R (first floor) 
 

297. Preventive maintenance decisions through maintenance optimization models: a case study

Sandrina Vilarinho, Isabel Lopes, José A. Oliveira

University of Minho, Portugal

Technology has always been a key driver of change in industry. The deployment of new technologies is determinant to enhance manufacturing systems availability, improve cost-effectiveness, and deliver better and more innovative products and services. Inevitably, maintenance, is influenced by those rapid technological changes. Those modifications strengthen today’s competitive environment, forcing enterprises to adopt practices and methods to optimize maintenance decisions and achieve maintenance excellence. One of the main challenges in the maintenance field is to achieve a high degree of control over maintenance activities. In this context, Computerized Maintenance Management Systems (CMMS) arise as a fundamental tool to support the maintenance strategies. Those systems process data to provide information that supports maintenance activities, including preventive maintenance decisions.

In industry, one of the most common preventive maintenance problems is to determine the best preventive intervention time of productive equipment, by minimizing or maximizing some interest criteria. Traditionally, the preventive replacement of parts or maintenance interventions are defined through the technician’s experience or equipment manufacturer recommendations, without the search for an optimal solution. Scientific approaches allow decision making to be based on facts acquired through real data analysis. In this case, maintenance interventions can be performed at predetermined intervals based on failure time analysis. This process includes failure analysis and the use of mathematical models to determine the optimal decisions in relation to an objective.

This paper reports the implementation of a procedure to support the planning of preventive interventions to be integrated in a CMMS of an automotive company. More specifically, it provides a basis to get a CMMS function that allows to obtain the optimal periodicity or preventive interventions, considering costs. In this paper, the procedure is discussed considering the necessary data and its proper organization and the critical factors for its implementation.

The crucial stages of the development method involve the analysis and reorganization of failures records in the existent CMMS adopting a failure tree structure to facilitate reliability study. In addition, all necessary steps to the reliability study must be defined to determine the optimal periodicity of preventive maintenance interventions. Finally, the method validation will be done to be later integrated in the information system.

The analysis of procedure implementation is based on failure data from a critical item in the manufacturing company. The developed procedure will contribute to improve equipment maintenance decisions and also to support maintenance activities, including, maintenance actions scheduling and spare parts management.


258. Research on Reliability Modeling of CNC System Based on Association Rule Mining

Guangpeng Liu, Chong Peng

Beihang University, China, People's Republic of

CNC system is the control center of CNC machine tools, and failure positions and failure causes of the CNC system are varied. CNC system itself manufacturing, assembly problems or performance degradation of components caused by failure, called associated failure; failure was caused by external factors such as maintenance reasons, improper installation, misoperation, which was known as non-associated failure and need eliminating in the counting process of reliability modeling. In order to improve the accuracy and validity of the reliability modeling and evaluation, the failure correlation factor is introduced into the reliability modeling of CNC system. The size of failure correlation factor can describe clearly the inter-dependent relationship between failure positions and failure causes, but the relevant literature about how to obtain fault correlation factor is less. This paper considers the data mining technology, sets up the failure time data set, analyzes failure positions and failure causes, uses Apriori algorithm to search the frequent itemsets, and obtains the association rules with minimum confidence. The failure correlation factor is obtained by the confidence degree between the failure positions and failure causes obtained by the association rules. In the process of CNC system reliability modeling, the failure correlation factor is introduced into the model, improving the reliability evaluation accuracy of the modified model for CNC system.


213. Effect of coefficient of thermal expansion (CTE) mismatch of solder joint materials in photovoltaic (PV) modules operating in elevated temperature climate on the joint’s damage

Osarumen Ogbomo1, Emeka H. Amalu2, N.N Ekere1, P. O. Olagbegi3

1University of Wolverhampton, United Kingdom; 2Department of Mechanical, Aerospace and Civil Engineering, School of Science and Engineering, Teesside University, Middlesbrough, Tees Valley, TS1 3BA, UK; 3Mechanical Engineering Department, Faculty of Engineering, University of Benin, Nigeria

With failure of solder joints (SJs) in photovoltaic (PV) modules constituting over 40% of the total module failures, investigation of SJ’s reliability factors is critical. This study employs the Garofalo creep model in ANSYS Finite Element Modelling (FEM) to simulate solder joint damage. Accumulated creep strain energy density is used to quantify damage. PV modules consisting of interconnections formed from different material combinations (silver, copper, aluminum, zinc, tin and brass) are subjected to induced temperature cycles ranging from -40 °C to +85 °C. Results show that zinc-solder-silver joint having the highest CTE mismatch of 19.6 ppm exhibits the greatest damage while silver-solder-silver with no mismatch possesses the least damage


110. A conceptual framework of knowledge conciliation to decision making support in RCM deployment

Flávio Piechnicki1,2, Eduardo De Freitas Rocha Loures1, Eduardo Alves Portela Santos1

1Pontifical Catholic University of Parana, Brazil; 2Federal Institute of Parana, Telêmaco Borba, 84269-090, Brazil

This paper proposes a conceptual framework that conciliates tacit and explicit information from the maintenance function, generating a new knowledge base used in analyzing and improving decisions in deploying a customized RCM (Reliability Centered Maintenance) model. The transformation of raw information into formal knowledge must generate personalized records in a single database, being available for the RCM deployment phases. By identifying trends and applying Process Mining techniques, hidden patterns and relationships can be uncovered. MCDM/A (Multi Criteria Decision Making/Analysis) methods support the decisions in the stages of RCM implementations. Improving maintenance strategies is an important approach in increasing system reliability and reducing costs.

 
3:10pm - 4:05pmKEY 2: Keynote Speech 2 (Chen-fu CHIEN)
Manufacturing big data analytics for smart production
Aula Convegni (first floor) 
4:05pm - 4:30pmCoffee break
Gallery at first floor 
4:30pm - 5:30pmSES 3.1: Robotics and Computer Integrated Manufacturing
Session Chair: Giovanni Berselli
Aula Convegni (first floor) 
 

379. Analysis of the energy consumption of a novel DC power supplied industrial robot

Ritvars Grebers1, Michele Gadaleta2, Arturs Paugurs1, Armands Senfelds2, Ansis Avotins1, Marcello Pellicciari2

1Institute of Industrial Electronics and Electrical engineering Riga Technical University; 2Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, Via Vivarelli 10, 41125 Modena Italy

The energy consumption and electrical characteristics of a novel direct current (DC) power supplied industrial robot are compared and analyzed with a state of the art alternating current (AC) supplied industrial robot. An extensive set of experiments show an important reduction of the total energy consumption for different electrical power profiles measured in various robot trajectories with specific working temperatures. The recuperated energy is also analyzed in the different scenarios. Experimental results show that a DC type robot can be up to 12.5% more energy-efficient than an equivalent AC type robot.


246. Energy Consumption Modeling of a Turning Table and Standardized Integration into Virtual Commissioning Tool Chain

Dominik Hauf1, Julian Kruck1, P. Paryanto2, Jörg Franke2

1Daimler AG, Germany; 2Institute for Factory Automation and Production Systems (FAPS), FAU Erlangen-Nuremberg, Egerlandstr. 7-9, 91058 Erlangen, Germany

Energy efficiency and flexibility are getting more and more important. Especially for automotive production an intelligent and sustainable use of energy is relevant due to increasing energy prices.

There are various ways to reduce energy consumption while the engineering of production lines and during the real production processes. However, the biggest impact on energy consumption arises from optimization steps in the digital process chain before start of production. Therefore, the best time for integrating optimization algorithms is before the real commissioning of a production line. Virtual Commissioning (vCom) includes the validation of programmable logic controller (PLC), the robot control and the 3D geometry. Nowadays vCom don’t provide data about energy consumption of a production line. Consequently, a new approach to simulate the energy consumption within the vCom tool-chain has to be developed.

To qualify VCom for the energy simulation it is necessary to add single energy models of each mechatronic component to the simulation system. For the set-up of energy models a detailed knowledge about the mechatronic component behavior is necessary. Often integrators of industrial automation components or plant manufacturers do not have the knowledge or the access to the knowledge. Suppliers do not provide detailed data about their components due to reasons of intellectual property. Therefore, in future the supplier himself should generate the mechatronic models. To exchange such models a global standard has established, the functional mock-up interface (FMI). FMI allows a protected allocation of simulation models (binary code) while the interface is defined in a XML document. One simulation model is specified as functional mock-up unit (FMU). This paper makes a suggestion for a standardized interface description of energy models to provide help for the suppliers.

Further, a guideline for a methodical development of energy models of automation components, like used in a turning table, is discussed and also the integration of such models into the vCom is presented.

A structured energy model of a turning table was generated. The model contains a powertrain and an inverter. While the powertrain is consisting of an electrical motor, a gearbox, a shaft and cam switches. For this purpose the object-orientated programming language Modelica was used. The validation of the simulation model shows that the results correspond with the measurements. The created model provides correct energy data within the vCom. This allows the use of the vCom for preparing and validating energy optimization steps.

In future, the energy consumption of whole production lines with all mechatronic components (robots, technologies and periphery) can be simulated within one integrated simulation environment.


281. Automatic modeling and simulation of robot program behavior in integrated virtual preparation and commissioning

Martin Dahl, Kristofer Bengtsson, Martin Fabian, Petter Falkm

Chalmers, Sweden

This paper presents a method where the behavior of a robot cell is automatically modeled based on existing robot programs and a simulation model of the cell. Robot programs from the shop floor are uploaded into a virtual manufacturing tool, and a formal model is then generated from the robot programs. Then, control logic is automatically calculated, and the fastest possible execution order is found by using the generated model to formulate an optimization problem. The result is continuously analyzed and validated by simulation in the virtual manufacturing tool.

 
4:30pm - 5:30pmSES 3.2: Smart Factories and Industrial IoT
Session Chair: Osiris Canciglieri Junior
Aula N (first floor) 
 

107. Mini-factories for close-to-customer manufacturing of customized furniture: from concept to real demo

Andrea Francesco Barni1, Donatella Corti1, Paolo Pedrazzoli1, Diego Rovere2, Giuseppe Lucisano3

1SUPSI, Switzerland; 2TTS - Technology Transfer System S.r.l., via Francesco d'Ovidio 3 - 20131 Milano; 3SCM Group S.p.a., Via Emilia, 77, 47921 Rimini RN, Italy

EU furniture market sector employs around 1 million workers in 130.000 companies generating an annual turnover of around EUR 96 billion. Recent financial crisis led to a contraction of production that, in the best cases, took companies back to production levels of ten years before. In order to respond to this trend European manufacturers, have to improve value proposition along the whole production chain by leveraging on new production paradigms able to satisfy customers' dynamic needs by increasing added value of their products. Furniture customisation has been generally accepted as one of the strategies providing a competitive breakthrough for European furniture industry to remain competitive. The revision of production systems, mandatory to enable the level of manufacturing flexibility required by this type of production paradigm, led to the definition of innovative manufacturing concepts. Mini-factories, defined as compact systems relying on the concept of “manufacturing cell” able to manage in an integrated way all the equipment and processes required to manufacture a specific product, are one of those. These compact production systems, despite responding to flexibility criteria have been shown, by themselves, to be not enough to answer the issues faced by current furniture market.

In this paper we describe a new concept of manufacturing system enabling flexible manufacturing of green personalized products close to the customer in terms of features offered, place of fabrication, time to deliver, and cost. The proposed system encompasses all the technological and organizational requirements enabling to bring design to manufacturing of customized products within shopping malls. Starting from a user friendly product configurator, customers select and configure their custom products working on several customization degrees, as set-up by product designers during basic design phase. The full IT integration among shop and factory software tools, and the direct connection with the compact manufacturing system displaced next to the shop, enables to automatically forward production orders, as soon as the customer approves the configured product. The innovative production system, fully automating manufacturing operations on a single working center (i.e. nesting, cutting, boring, edge-banding), enables products’ manufacturing relying on just one production operator per shift. Just in time production and a short and flexible supply chain enable to keep stock at a minimum.

The integration of the whole system and relative testing has been carried out within Centro Brianza, one of the most relevant shopping mall in Milan, for the duration of 15 days. In this period customers had the possibility to access the shop, configure their products and see them manufactured in quasi-real time. The promising results of the demonstration activity pave the way for further exploration of the proposed concept.


241. Integration and deployment of an industrial architecture for the PERFoRM project

Giacomo Angione1, José Barbosa2,3, Frederik Gosewehr4, Paulo Leitao2,5, Daniele Massa1, João Matos6, Ricardo Silva Peres6, André Dionisio Rocha6, Jeffrey Wermann4

1AEA s.r.l. - Loccioni, Italy; 2Polytechnic Institute of Bragança, Campus Sta Apolónia, 5300-253 Bragança, Portugal, email: {jbabrosa, pleitao}@ipb.pt; 3NESC-TEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal; 4University of Applied Sciences Emden/Leer, German, email: {frederik.gosewehr, jeffrey.wermann}@hs-emden-leer.de; 5LIACC – Artificial Intelligence and Computer Science Laboratory, University of Porto, Portugal; 6CTS UNINOVA, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, email: jp.matos@campus.fct.unl.pt, {ricardo.peres, andre.rocha}@uninova.pt

To meet flexibility and reconfigurability requirements, modern production systems need hardware and software solutions which ease the connection and mediation of different and heterogonous industrial cyber-physical components. Following the vision of Industry 4.0, the H2020 PERFoRM project targets, particularly, the seamless reconfiguration of robots and machinery. This paper describes the implementation of a highly flexible, pluggable and distributed architecture solution, focusing on several building blocks, particularly a distributed middleware, a common data model and standard interfaces and technological adapters, which can be used for connecting legacy systems (such as databases) with simulation, visualization and reconfiguration tools.


374. A framework of a smart injection molding system based on real-time data

Hwaseop Lee1, Kwangyeol Ryu1, Youngju Cho2

1Pusan National University, Korea, Republic of (South Korea); 2Manufacturing System R&D Team, Korea Institute of Industrial Technology, 55 Danggok 3-gil, Ipjang-myeon, Cheonan-si, Chungcheongnam-do 331-825, South Korea

The manufacturing industry has been facing several challenges, including sustainability, performance and quality of production. Manufacturers attempt to enhance the competitiveness of companies by implementing CPS (Cyber-Physical Systems) through the convergence of IoT(Internet of Things) and ICT(Information & Communication Technology) in the manufacturing process level. However, a CPS platform (or Smart factory in other words) or a framework is composed of different types of data acquisition/handling method, decision making rules and functions depending on the characteristic of the manufacturing company. In this paper, we propose a smart injection molding system framework based on real-time manufacturing data considering the characteristics of injection molding processes, modules that compose the framework, and their detailed functions. This paper is expected to be used as a guideline to increase the market competitiveness of injection molding industry and support the construction of a smart factory in preparation of Industire 4.0.

 
4:30pm - 5:30pmSES 3.3: Product and Process Design
Session Chair: Sara Mantovani
Aula O (first floor) 
 

30. A Critical Review of Design for Reliability - A bibliometric analysis and identification of research opportunities

Lucas Pagani, Milton Borsato

Federal University of Technology - Parana, Brazil

This paper presents a hierarchical heuristic to balance the workloads among multiple identical high-speed revolver-head gantry-type surface mount technology (SMT) machines in a printed circuit board (PCB) assembly line. The nozzle assignment, the component allocation, and the single machine optimization decisions are made with the objective of minimizing the assembly cycle time. An integer programming mathematical model is developed, and a deterministic hierarchical heuristic algorithm is proposed to solve this NP-hard problem efficiently. The experiment results show that the proposed heuristic algorithm reduces the cycle time by 6.94% on average compared to the industrial solutions.


313. Transforming ETO Businesses with Enhanced PLM Capabilities

Antti Juhani Pulkkinen1, Simo-Pekka Leino2, Jorma Papinniemi3

1Tampere University of Technology, Finland; 2VTT Technical Research Centre of Finland Ltd, P.O. Box 1000, FI-02044 VTT, Finland; 3Lappeenranta University of Technology, P.O.Box 20, FI-53851 Lappeenranta, Finland

This paper studies the transformation of business with enhanced Product Lifecycle Management (PLM) capabilities. The material for the research comes from a project conducted with public private partnership. The four industrial companies that we studied engineer and/or manufacture highly customized products in low volumes with globally distributed networks. This is an industrial context, which requires specific PLM capabilities. The capabilities include five areas and the new generation of software products supporting.

First capability is business oriented PLM implementation models, which enable companies to plan, deploy and benefit from a PLM roadmap for managing a business producing low volume and high variety products more systematically. Within the project it was estimated that the business impacts of PLM roadmap decrease lead-time even by 20% for every repeated process is enabled by shared data modules on the repeatability of projects and earlier product-related data.

The second capability is broad re-use of product knowledge and design automation. From the project experiences, it can be estimated that systematic design re-use and automation save thousands of engineering hours over a period of 0-3 years if the capability will be broadly utilized as a company-wide means of engineering industrialization.

Third PLM capability, enhanced enterprise change management (ECM+), is a set of novel means that cover the life-cycle, networks and product types of a company. We focused the first two in the project, which meant proactive change management in product development and change management as defined in CMII standard with released products. Based on real data, we analyzed that systematic change processes, review practices and digital product models enable substantial savings in time and costs by preventing material shortages and errors (15-25%) from progressing to production and procurement. This is supported by the expanded 3D (3D+) models and intermediary virtual prototyping (IVP) that in itself is the fourth PLM capability, which can be utilized in many different positions over the product lifecycle. 3D+ and IVP enable capturing and transforming product knowledge from all stakeholders, thus design and validation of product’s downstream properties and processes already in virtual stage. 3D+ and IVP models structure and conceptualize value creation mechanisms and preconditions for PLM and digitalization of manufacture.

Location independent manufacturing and supply (LIMS) is a PLM capability that will enable new ways of managing factory plant and technology projects supported by new PLM platform based solutions. Competitive advantage for project and lifecycle business can generate substantial growth and profit in the future, when implemented.

The new generation of software is aimed for the enhancing of collaboration within networks, design automation, and PLM system integration. In the software development, the requirements of the specific industrial context were being collected, analyzed and taken into account. All of the three vendors delivered new versions of their software.

The estimations of the business benefits of PLM capabilities are based on the experiences of industrial experts and our analysis of the situation in the companies before and after the project. The PLM capabilities support the transformation of other companies in similar industrial context.


387. Digital Continuity in Manufacturing

Adriano Garella

Dassault Systèmes, Italy

Today new trends creating opportunities in manufacturing: automation, data collection from smart sensors, decision support and operational user experiences, customer data, design models, all come together. In addition, there are ongoing technology changes increasing the viability of cloud computing in manufacturing, new mobile form factors for users, and new uses of big data. Digital continuity is the ability to use digital information in the way that you need, for as long as you need. If you do not actively work to ensure digital continuity, your information can easily become unusable. Digital continuity is about making sure that your information is complete, available and therefore usable for your business needs.

We must connect innovation with the product delivery, all devices and all the users who contribute to their company’s mission of providing goods and services. Connecting engineering with manufacturing is one key linkage. However, we must also connect the physical world and integrate to machinery and equipment. In our supporting our customers, we’ve been doing this for years - and it is now called edge computing. With new technologies evolving and new terminology (Industrial Internet of Things, Internet of Things), there are new ways to collect data from automation and equipment; and some of the technology allows for the creation of smart devices to be better orchestrated by decision support solutions.

 
4:30pm - 5:30pmSES 3.4: Manufacturing Operations, Supply Chain and Logistics
Session Chair: Teresa Pereira
Aula P (first floor) 
 

237. A TCO model for supporting the investment analysis of industrial plants

Marco Mandolini, Eugenia Marilungo, Michele Germani

Università Politecnica delle Marche, Italy

In the current industrial context, where processes are extremely flexible to meet the market demand and companies pay more and more attention to satisfy the customers’ needs, the traditional cost assessment methods are too restrictive because they consider only the manufacturing phase of a product. A novel lifecycle approach that considers also the cost incurred during the product use and end of life phases is required. The Total Cost of Ownership (TCO) is the method conceived for solving this problem and it is becoming very attracting for its long term advantages in terms of cost saving. For instance, when an investment manager approaches and assesses a new investment (e.g. production machine, utility, production line, building), he needs to know the lifecycle costs of that item, in order to optimize the long-term costs. Moreover, during the investment analysis for a new asset (or revamping of an existing one) it is crucial for the investment manager knows the life cycle data for the asset of their suppliers: this is the crucial aspect of applying the TCO method for preventive analysis.

The scientific and industrial literature contains several applications of such a method. The first branch of research applies the TCO method during the procurement phase of a product/service as a support for the supplier selection. The main limitation of such approaches is that they are not integrated with the design phase of a product nor they are applied for the industrial assets. The TCO method is also used for the consumptive analysis of a product/process, once it is running at the facility of the owner, for evaluating future scenario such as revamping or substitution. The use of the TCO method for the preventive analysis is not well investigated.

The paper presents a TCO model for the preventive analysis of industrial assets, which can be used during the design phase, for supporting the asset configuration, and during the procurement phase, for supporting the supplier selection and negotiation. At the design phase, the model foresees a configuration framework, which allows the designer to configure the asset by selecting its feature in accordance to the product to realize. The model inform the designer about the preventive TCO of each possible solution (a solution consists of a combination of supplier and asset technology). At the procurement phase, the model allows the investment manager to select the best supplying strategy by simulating and optimizing different scenarios. A scenario consists of an asset technology, supplier, production plant and useful asset life.

To foster the TCO model application, the authors developed a preliminary software application distributed to designers and investment managers. The model and relative software tool is under test by an Italian company of the agribusiness sector, which aims to optimize the design and procurement phase of their assets.


243. Applications’ Integration and Operation Platform to Support Smart Manufacturing for Small and Medium-sized Enterprises

Chanmo Jun1, Ju Yeon Lee1, Joo-Sung Yoon2, Bo Hyun Kim1

1KITECH, Korea, Republic of (South Korea); 2Smart Manufacturing Technology Group, Korea Institute of Industrial Technology, 89, Yangdaegiro-gil, Giro-ri, Ipjang-myeon, Seobuk-gu, Cheonan-si, Chungcheongnam-do, 31056, South Korea

Many developed countries are making various efforts to innovate their own manufacturing industries, through initiatives such as Manufacturing innovation 3.0, Industry 4.0, and Manufacturing 2025. Innovation in the manufacturing industry, represented by the so-called “smart factories,” is being developed through the latest technologies such as Internet of Things (IoT), Cloud, and Big data. However, as the application of these technologies requires a lot of cost and time, small and medium-sized enterprises are often hampered in their efforts to take full advantage of them. For an enterprise that operates a manufacturing information system, the integrated management of information between systems is essential to the application of a new technology. If the enterprise lacks the relevant experts, it will have difficulty applying a new technology in the field. This study suggests the application of a cloud-based Applications’ Integration and Operation Platform in order to resolve those problems. The Applications’ Integration and Operation Platform must accept a large volume of data at IoT-based manufacturing fields, interconnect between manufacturing fields and Applications’ Integration and Operation Platform, and provide application contents in the form of service. The suggested study contents are applied to a company that produces plastic injection models to verify their effects. It is expected that this study can be used as a reference model for applying smart factory technologies to other small and medium-sized enterprises in the future.


80. Organizational Performance and Indicators: Trends and Opportunities

Fernanda Antunes Silva, Milton Borsato

UTFPR, Brazil

Given the current competition into markets, it’s necessary for companies to monitor their practices and results in order to ensure competitiveness. To survive these challenges and compete successfully, organizations need to monitor processes through key performance indicators (KPIs). Currently, indicators are analyzed in an isolated way within the organizations. Therefore, it’s important that companies use a harmonization approach both in the creation and monitoring process of indicators. Based on it, this article carries out a research to find the state of the art and the research opportunities. To do that, a bibliographic portfolio was constructed and bibliometric and systemic analyzes were performed.

 
4:30pm - 5:30pmSES 3.5: Reliability and Predictive Maintenance
Session Chair: Michele Calì
Aula Q (first floor) 
 

3. Decentralized Data Analytics for Maintenance in Industry 4.0

Eckart Uhlmann1,2, Abdelhakim Laghmouchi1, Claudio Geisert1, Eckhard Hohwieler1

1Fraunhofer Institute for Production Systems and Design Technology, Germany; 2Institute for Machine Tools and Factory Management IWF - Technische Universität Berlin, Germany

Due to the increased digital networking of machines and systems in the production area, large datasets are generated. In addition, more external sensors are installed at production systems to acquire data for production and maintenance optimization purposes. Therefore, data analytics and interpretation is one of the challenges in Industry 4.0 applications. Reliable analysis of data (e.g. internal and external sensors) and information, such as system-internal alarms and messages produced during the operation, can be used to optimize production and maintenance processes. Furthermore, based on the data analytics, information and knowledge can be extracted from those raw data and used to develop data-driven business models and services, e.g. offer new availability contracts for production systems. This paper illustrates a concept for decentralized data analytics based on a smart sensor networks. The basic elements of this concept are the single-board computers, such as Raspberry Pi 3 and MEMS (Micro-Electro-Mechanical Systems) vibration sensors and standard communication technologies. Moreover, the decentralized data analytics by means of machine learning algorithms for data processing and pattern recognition, such as support vector machines will be presented using exemplary applications.


100. Mining shop-floor data for preventive maintenance management: integrating probabilistic and predictive models

Edson Ruschel, Eduardo Alves Portela Santos, Eduardo de Freitas Rocha Loures

Pontifical Catholic University of Parana, Brazil

Production processes are subject to degradation in their machinery and consequently loss of yield and quality may occur. Maintenance strategies and policies are constantly growing and developing to meet the requirements of high reliability and availability of resources in the production process. Among maintenance policies and strategies, it is possible to cite preventive maintenance, supported by the growing number of tools and information available that guarantee a reliable evaluation of the processes behavior. This type of maintenance covers regular inspections based on estimates of the machinery condition, preventing certain failures before they occur. Although literature and practical experience have proven that preventive maintenance is more effective than corrective maintenance, poorly determined intervals can still lead to high costs and a significant reduction in equipment availability. In order to avoid these issues, an optimized diagnostic analysis of the production process can be performed, allowing a better possible evaluation of the future behavior of the machinery involved. In this area, effective collection of shop-floor data is required, as well as adequate tools and techniques to transform this data into useful information for the manager or decision maker. Information extracted from event logs can be used in probabilistic and predictive models, effectively aiding in the evaluation of process behavior. The process mining techniques are approached in the present work to obtain a process model, used for the construction of a probabilistic model in Bayesian Networks (BN). The BN model outputs are frequency probabilities of the process activities that will feed the Autoregressive Integrated Moving Average (ARIMA) models. Preventive maintenance intervals are simulated between the production activities and the sum of the cycle times variations are compared until the best maintenance interval is found. The BN model also allows simulating variations in the productive activities frequency, re-feeding the ARIMA predictive models and providing new inferences for the preventive maintenance intervals. To validate the proposed methodology, an applied study is performed to a database collected from a lathe machine (CNC Turning) through a FIS, installed in an automobile industry. Simulations with increase and reduction in the machining activity frequency were performed and the values in the predictive models outputs are compared to the real values in the event log. For the application of this methodology is required a reliable collection of shop-floor data and a correct standardization of the event log, avoiding the existence of data that diverge from the real process behavior.


236. Data mining and machine learning for condition-based maintenance

Riccardo Accorsi1, Riccardo Manzini1, Pietro Pascarella2, Marco Patella2, Simone Sassi1

1Department of Industrial Engineering, Alma Mater Studiorum Bologna, viale del Risorgimento 2 – 40136 Bologna (Italy); 2Department of Computer Science and Engineering, Alma Mater Studiorum Bologna, viale del Risorgimento 2 – 40136 Bologna (Italy)

Complex production systems may count thousands of parts and components subject to multiple physical and logical connections and interdependencies. This level of complexity inhibits the traditional and statistically-based approach to reliability engineering, failure prediction and maintenance planning.

In the era of the Industry 4.0, emerging technologies, e.g. Radio Frequency Identification (RFID), Micro-Electro-Mechanical Systems (MEMS), Supervisory Control and Data Acquisition (SCADA) systems, Product Embedded Information Devices (PEID), represent more and more performing and available solutions to collect and monitor operating conditions of several components and functional groups, parts of such production systems.

The existing ICT solutions simplify the collection of large amount of data from on-field. The aim is to collect the right amount of data in order to predict in advanced the performance of the production system including the health/failure status. Is it possible to prevent an event of failure? Which is the role of data mining and machine learning techniques to support decision making in maintenance planning and execution? This paper introduces a number of state-of-the-art data analytics models and methods that can be profitably used for decision making in general, and, specifically, in maintenance engineering. Some numerical examples inspired to real case studies are illustrated demonstrating the effectiveness of such models and methods.

 
4:30pm - 5:30pmSES 3.6: Quality engineering and management
Session Chair: Paul-Eric Dossou
Aula R (first floor) 
 

204. Cost effective quality assessment in industrial parts manufacturing via optical acquisition

Francesco Malapelle1, Diego Dall'Alba1, Denis Dalla Fontana2, Ivano Dall’alba2, Paolo Fiorini1, Riccardo Muradore1

1University of Verona, Italy; 2Modelleria Pozzan - Via del Progresso 1/20, 36015 Schio VI, Italy

Dimensional control is a key component in today’s Industry 4.0.The capability to verify that the designed geometry meets the project requirements in terms of expected dimensional constraints imposed by the specific part functional role is an ongoing challenge during the manufacturing process.

In an effort to verify product form, fit and function, the majority of companies are adopting traditional measurement techniques, e.g. using coordinate-measuring machines (CMM). These techniques have proven to be highly accurate on parts that feature simplistic shapes with easy to measure spots (e.g. circular holes, edges with regular thickness and, in general, regular geometries). Unfortunately product verification becomes a very costly and time consuming process when the parts present complicated characteristics, such as contoured surfaces, heavily featured geometry and product assemblies.

Optical 3D scanning techniques are less accurate than traditional methods but they have proven to be both an accurate and a cost-effective alternative solution to the problem of dimensional information estimation, allowing to create measuring reports that are more meaningful, complete and informative and that can be delivered in a visual fashion (e.g. full color rainbow plots, sectional comparisons), or as traditional CMM-style reports.

Today, many of the industrial sectors have implemented 3D scanning technologies to address their inspection and quality assurance requirements, but in many cases highly accurate systems are not affordable for small or medium enterprises (SME). This makes them less competitive in the upcoming Industry 4.0 revolution. There is a wide gap, in both cost and measuring performance, between high-end systems and affordable solutions available for SME.

Therefore, the design and development of a cost-effective and reliable 3D scanning and measurement system suitable for SME is a priority for allowing them to tackle the problem of quality control as bigger stakeholders.

The part of the system that most influences the accuracy is the available 3D scanning system. In this work we adopt a low-cost optical acquisition system based on two cameras and a projector mounted on a tripod; the same setup is used in several high-end measuring systems. We compare the proposed system with other optical 3D scanning systems in terms of cost and accuracy: a RGB-D time of flight sensor, a state-of-the-art photogrammetry reconstruction software, and a professional 3D scanner.

We provide quantitative results obtained on a synthetic mechanical component manufactured by our industrial partner having challenging characteristics, such as holes, protuberances, indentations, curved surfaces and low-visible areas. The original CAD model is used as ground truth for a fair comparison in terms of standard point cloud and mesh distances. Moreover we provide qualitative results on a real mechanical part, using the same systems. The results indicate that our system is a reliable source of dimensional information that will be affordable to all those industries that cannot buy expensive high-end systems.


309. Solving quality problems in tire production preparation process: a practical approach

Bruno Miguel Amorim Barbosa1, Maria Teresa Pereira1,2, Francisco G. Silva1, Raul Campilho1

1Instituto Superior de Engenharia do Porto, Portugal; 2CIDEM – Centro de Investigação e Desenvolvimento em Engenharia Mecânica, Porto 4200-072, Portuga

This work was carried out in Continental tire factory in the APEX machines production process, with the propose of improving APEX performance and the produced product quality rate. Main possible causes of defects generation was identified and proposals for improvement to enhance the proper functioning of the APEX production process was also developed. Applying Six Sigma, the identification of the variables that influence the quality of the production was obtained. DMAIC cycle (Define, Measure, Analyse, Improve, Control) was applied in the process analyse. This enabled a structured analysis and the identification of different causes that negatively affect the process in study and consequently the identification of opportunities for improvement.

With the help of the DMAIC method a series of experiments was developed in order to achieve improvements in product quality rate and process control and stabilization.


149. Reliable and flexible Quality Management Systems in the automotive industry: monitor the context and change effectively

Luis Miguel Fonseca, Jose Pedro Domingues

Instituto Superior de Engenharia do Porto, Portugal

The automotive industry is facing considerable challenges with increased competition and more brands, models and complex vehicles, tighter regulatory requirements (e.g., emissions), and the need to manage global supplier networks with shorter development cycles.

To respond to customer demands and to improve business performance, more than 1 million organizations, of all activity sectors worldwide, have implemented ISO 9001 International Standard Quality Management Systems (QMS).

With the purpose of ensuring that ISO 9001 remains actual in a world of increasingly complexity and interconnection, ISO issued the revised ISO 9001:2015, with novel and reinforced approaches. This lead to the new IATF 16949 standard for the automotive industry, that should be comprehended as a supplement to and used in conjunction with ISO 9001:2015. While ISO 9001:2015 is more focused on the organization and its customers (and relevant interested parties that influence the quality of the organization products), IATF 16949 greater emphasizes the OEM (Original Equipment Manufacturer) and statutory and regulatory requirements, emphasizing defect prevention and the reduction of variation and waste in the supply chain.

The ratio of supplier added value in the automotive industry shows a consistent growth from 56% in 1985 to 82% in 2015 (Statista, 2016). QMS are a key requirement to ensure a competent supplier network, with properly selected and qualified suppliers.

This research goal is to identify relevant dimensions for organizations to effectively improve (either by continuous incremental improvement or by disruptive breakthrough), a study of the organizations that have already implemented and be independently audited against ISO 9001:2015, was carried out with IRCA ISO 9001:2015 Registered Auditors, all over the world.

Although the auditee organizations were not restricted to the automotive sector, due to the horizontal characteristics of the automotive industry supply chain, this could be a preliminary input for the industry. The online survey yielded 393 valid replies, from auditors from 71 countries, and three variables were evaluated with a Likert scale:

- “Change management” has been successfully implemented by the auditee organizations?

- “Understanding the organization and its context” has been successfully implemented by the auditee organizations?

- “Improvement” has been successfully implemented by the auditee organizations?

Sample normality was confirmed trough Kolmogorov-Smirnov Test and the hypotheses were tested by using Pearson Correlation coefficient. The findings show the existence of a strong positive correlation between:

- The capability to understanding the context and both the ability to change and the achievement of improved performance and results;

- The ability to change (plan, design, implement and control change) and the achievement of improved performance and results.

These conclusions highlight the need for the automotive industry OEM and Suppliers to properly monitor the organizational (internal and external) context and identify the key issues that affect the ability of their QMS to deliver quality products, and to plan, design, implement and control change in an effective and timely manner, within the whole supply chain. These can be major contributors for the industry ecosystem improved performance and results.

 
7:30pm - 10:30pmWelcome Social Event
Via Paolo Ferrari, 85 - Modena
Meeting Point at Museo Enzo Ferrari at 7.30 (PM) - walking distance from San Geminiano (1,4 km - 15 minutes) and from all hotels in the Modena downtown.
Indications on Google Maps: https://goo.gl/maps/e9qf4hV1gqu
Museo Enzo Ferrari 
Date: Wednesday, 28/Jun/2017
8:30am - 9:00amRegistration & Welcome Coffee
Complesso San Geminiano 
9:00am - 10:00amSES 4.1: Digital Product and Process Development
Session Chair: Milton Borsato
Aula Convegni (first floor) 
 

161. Quality-predictive CAM simulation for NC milling

Christian Brecher, Frederik Wellmann, Alexander Epple

Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Germany

Milling processes are primarily rated by productivity and resulting product quality. However, while modern CAM and NC simulation systems are capable of predicting productivity indicators (e.g. cycle times), no explicit forecast of the resulting product quality with respect to individual workpiece tolerances is possible, yet. On that account, a first-time-right approach is introduced, which enhances the physics-based modelling behind existing simulations by describing the impact of machine tool, fixture, cutting tool and technology parameters on part quality. It is shown that influences of workpiece deformation, tool deflection and geometrical precision can be represented context-sensitively for prismatic part machining.


18. Virtual maintenance simulation for socially sustainable serviceability

Margherita Peruzzini1, Fabio Grandi1, Marcello Pellicciari1, Claudia Campanella2

1University of Modena and Reggio Emilia, Italy; 2CNH Industrial, Ergonomics – HMI, Design Analysis & Simulations, Viale delle Nazioni 55, 41100 Modena, Italy

In order to achieve more sustainable development processes, industries need not only to improve energy efficiency and reduce costs, but also to increase the operators’ wellbeing to promote social sustainability. In this context, the present research focuses on the definition of a methodology based on human-centred virtual simulation to improve the social sustainability of maintenance tasks by enhancing system design and improving its serviceability. It is based on the operators’ involvement and the analysis of their needs from the early design stages on virtual mock-ups. The methodology proposed merges a protocol analysis for human factors assessment and an immersive virtual simulation where human-centred serviceability simulations can be used during design phases. To demonstrate the effectiveness of the proposed method, an industrial use case has been carried out in collaboration with CNH Industrial.


158. A 4M approach for a comprehensive analysis and optimization of manual assembly lines

Claudio Favi1, Michele Germani2, Marco Marconi2

1Università degli Studi di Parma, Italy; 2Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, Ancona, Italy

Different Design-for-X (DfX) methods have been developed in recent years to support the design process and the product engineering stage. Methods and tools for efficient Design-for-Assembly (DfA) are well-known techniques, widely used throughout many large industries. DfA supports in the reduction of product manufacturing costs and it potentially leads greater benefits than a simple reduction in assembly time.

DfA techniques have been developed since the early 1980’s and among them the most famous one is certainly the Boothroyd and Dewhurst method (B&D), widely accepted and used in industrial contexts. The B&D method allows measuring the complexity of assemblies and deriving quantitative results. However, this method is rather laborious and, in most cases, it only focuses on the product design, missing to provide a holistic overview of the assembly line, workstations, assembly tasks, etc.

In this context, this paper proposes a more comprehensive approach to overcome the above-mentioned weak points and to optimize the assemblability of complex mechanical products, by taking into account all the aspects involved in the manual assembly. The proposed 4M design for assembly approach is based on the examination (recording) and analysis of each single task of an existing manual assembly line. The 4M concurrently considered by the approach are: (i) Method – Assembly issues related to the product and components design and geometry; (ii) Machine – Assembly issues related to the workstation layout, tools arrangement and ergonomics aspects; (iii) Man – Assembly issues related to the workers, which includes ambiguous assembly instructions, skills and experiences, training, etc.; (iv) Material – Assembly issues related to the tools and equipment used for the manual assembly operations.

The step beyond the current state of the art is the clear identification and classification of manual assembly issues by means of a systematic approach able to split these issues in four specific categories (Method, Machine, Man and Material). In this way, the re-design process is assisted and designers are guided during the decision-making process for the optimization of assembly time and costs. The final goal of this work is the concurrent improvement of the product design, the workstation and equipment ergonomics, as well as the assembly tasks.

Within this work, a complex assembly product (electric spindle motor) has been selected to validate the proposed approach. At first, the product and relative assembly line have been analysed following the proposed 4M approach, in order to highlight the most relevant issues. Successively, different re-design actions have been implemented to mitigate the criticalities related to product design (Method), workstation (Machine), assembly operations and instructions (Man) and tools (Material). The results obtained with the new product configuration have been finally compared with the performances of the original design configuration. Important improvements have been highlighted in terms of relevant parameters of the assembly process, such as assembly time, number of needed assembly operations, takt time of the assembly line and overall manufacturing costs.

 
9:00am - 10:00amSES 4.2: Production Planning and Scheduling
Session Chair: Sang Won Yoon
Aula N (first floor) 
 

363. Decision trees for supervised multi-criteria inventory classification

Francesco Lolli1, Alessio Ishizaka2, Rita Gamberini1, Elia Balugani1, Bianca Rimini1

1University of Modena and Reggio Emilia, Italy; 2Centre of Operations Research and Logistics, Portsmouth Business School, University of Portsmouth, Richmond Building, Portland Street, Portsmouth PO1 3DE, United Kingdom

A multi-criteria inventory classification (MCIC) approach based on supervised classifiers (i.e. decision trees and random forests) is proposed, whose training is performed on a sample of items that has been previously classified by exhaustively simulating a predefined inventory control system. The goal is to classify automatically the whole set of items, in line with the fourth industrial revolution challenges of increased integration of ICT into production management. A case study referring to intermittent demand patterns has been used for validating our proposal, and a comparison with a recent unsupervised MCIC approach has shown promising results.


338. An efficient order-picking route planning based on a fuzzy set method with a multiple-aisle in a distribution center

Teng-Sheng Su, Ming-Hon Hwang

Chaoyang University of Technology, Taiwan

In this paper, we propose a methodology based on the fuzzy set theory to solve the order-picking route planning problem with a multiple-aisle in a distribution center. Unlike traditional route planning strategies that only cope with quantitative data, fuzzy set-based methods provide proper mechanism for expressing planners’ linguistic terms to determine the level of factors that affect the order-picking route planning. A proposed order-picking route planning procedure that applies the fuzzy logic and the fuzzy clustering algorithm is presented here. The objective aimed to achieve is to reduce the traveling distance and time of order picking on the dynamic and elaborate order fulfillment operations. An example is given to illustrate the proposed route planning procedure. It is our hope that the proposed fuzzy approaches from this study can assist order pickers to deal with both quantitative and linguistic factors in improving the overall performance of their order-picking operations.


167. Real-Time Dispenser Replenishment Robust Optimization Based on Receding Horizon Control

Husam Dauod, Haifeng Wang, Nourma Khader, Sang Won Yoon, Krishnaswami Srihari

State University of New York at Binghamton, United States of America

This paper presents a real-time robust optimization approach to enhance drug dispenser replenishment planning in central fill pharmacy (CFP) systems. Dispenser replenishment is a critical process that influences the efficiency of CFP automated operations. However, dispenser replenishment planning depends on various stochastic variables such as demand, counting speed, and medication size. These variables increase the complexity of inventory planning, especially when the demand volume is high. The objective of this research is to find a real-time dispenser replenishment strategy by applying robust optimization and receding horizon control approaches. A mixed integer programming model is proposed to minimize the total replenishment process cost, which includes the costs of inventory holding, shortage, device setup, and operation. Uncertainties in demand and process operation times are captured using box uncertainty sets to enhance the model robustness. A receding horizon control mechanism is applied to divide the practical situation into separate time windows to reduce the computational burden and enhance the solution’s quality. The model is tested based on actual CFP data. The impacts of uncertainty and receding horizon control settings on total operation cost are investigated and discussed. The results indicate that the proposed model not only gives robust recommendations for dispenser replenishment planning, but also enhances the efficiency of the real-time decision making process.

 
9:00am - 10:00amSES 4.3: Collaborative Robotics in Smart Manufacturing
Session Chair: Pedro Neto
Aula O (first floor) 
 

89. Collaborative Robots in E-Waste Management

Esther Álvarez de los Mozos1, Arantxa Renteria2

1University of Deusto, Spain; 2Tecnalia Research & Innovation, Derio 48160, Spain

Nowadays manufacturing companies are going through an increasing public and government pressure to reduce the environmental impact of their operations. Customers are changing their attitude towards the products they buy considering not only the acquisition cost but also how the product was made and in which labour conditions, as well as how it is disposed at the end of its life cycle. There are recent examples such as the VW emissions scandal, variations in oil prices depending on the use of fracking technologies for extraction, or lack of raw materials for the manufacturing of high-tech devices causing environmental and social problems in third countries. They show that the consequences of ignoring the environmental effects of the manufacturing operations cause unexpected results in the acceptance of a product.

Until recently, and due to the economic crisis, the quest for higher employment rates seemed to fade the role of the circular economy, green manufacturing and use of recycled elements as source of raw materials. The aim was to encourage natural resource extraction and manufacturing activities regardless of their environmental impact, seeking for the reduction of unemployment. But what used to be taken as restrictions on economic activities in the past, is increasingly regarded as an essential element for the individual preferences and levels of quality of life, and thus emerges as new opportunities for development and improving competitiveness. Now the environment plays a core role in the people´s decisions: where to live, what to consume, how to produce.

The circular economy requires new production schemes, we cannot afford to waste scarce materials and resources. But when dealing with waste from electric and electronic equipment (WEEE), the barriers for the success of their recycling (technical and economic) are the difficulties in the classification and disassembly of components. The manual process is financially prohibitive and the full automation of the activity has not been achieved due to the lack of uniformity of the disposed devices. A halfway solution is to let a human operator and a robot share the process. New developments in collaborative robots allow for a close cooperation between humans and robots in a common working place, without fences between them. Thus the complexity of material and component identification could rely on the human side, while the more force demanding (and dangerous) tasks could be carried out by a robot. Current technical problems in the identification, classification, disassembling and manipulation of WEEE could be overwhelmed by a combination of robotized and manual operations, where the human teach a robot where to cut, separate parts, and the machine performs the low skilling operations. In addition, a smart transfer of tools and components must be achieved between human operator and robot.

The goal of this research is the optimization of the recycling process of electronic equipment, applying technical and economic criteria, taking into account new developments in collaborative robotics, and generating a model according to a dismantling strategy and degree of recovery that optimizes the profitability of the recycling.


78. An AR-based Worker Support System for Human-Robot Collaboration

Hongyi Liu, Lihui Wang

KTH-Royal Institute of Technology, Sweden

In human-robot collaborative manufacturing, industrial robots would work alongside the human workers who jointly perform the assigned tasks. Recent researches revealed that recognised human motions could be used as input for industrial robots control. However, the information feedback channel from industrial robots to human workers is still limited. In response to the requirement, this research explores the potential of adopting augmented reality (AR) technologies in a worker support system for human-robot collaborative manufacturing. The robot commands and worker instructions can be virtually augmented for human workers intuitively and instantly. The designed AR-based worker support system is demonstrated by a case study.


181. Human behavior and hand gesture classification for smart human-robot interaction

Nuno Marques Mendes, João Ferrer, João Vitorino, Mohammad Safeea, Pedro Neto

University of Coimbra, Portugal

This paper presents an intuitive human-robot interaction (HRI) framework for gesture and human behavior recognition. It relies on a vision-based system as interaction technology to classify gestures and a 3-axis accelerometer for behavior classification (stand, walking, etc.). An intelligent system integrates static gesture recognition recurring to artificial neural networks (ANNs) and dynamic gesture recognition using hidden Markov models (HMM). Results show a recognition rate of 95% for a library of 22 gestures and 97% for a library of 6 behaviors. Experiments show a robot controlled using gestures in a HRI process.

 
9:00am - 10:00amSES 4.4: Quality engineering and management
Session Chair: Paul-Eric Dossou
Aula P (first floor) 
 

259. Application of SPC and quality tools for process improvement

Sérgio Dinis Sousa1, Nuno Rodrigues2, Eusébio Nunes1

1ALGORITMI Research Center, Campus de Gualtar, University of Minho - DPS, 4710-057 Braga, Portugal; 2Production and Systems Department, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal

1. Introduction

The implementation of quality tools and methodologies is necessary to reduce defective items, and thus reducing the overall quality costs. This can be achieved by reducing process variability, allowing further increase in organization’s competitiveness and sustainability.

The quality function within a company ensures compliance with product specifications and implements process improvements [1], to produce with greater efficiency.

This work was developed at a metal parts production company with the objective of improve the company's production through the application of quality methodologies and tools. From a large set of items produced by the company it was selected as object of this study the one that presented higher percentage of nonconformities. These nonconformities were related to the non-compliance with the specification of one variable (dimension 51).

2. Methodology

The methodology used in this work can be structured in the following steps:

Step 1: Sample data collection of the critical variable in the production phase;

Step 2: Construction of X-s charts [3];

Step 3: Assessment of process capability (calculation of Capability index Cpk);

Step 4: Analysis of the control charts and, comparison with historical data obtained during pre-production.

Step 5: Identify assignable causes of variability. If necessary, conduct Measurement System Analysis;

Step 6: Development of improvement proposals, to reduce variability of the critical variable.

3. Results and Discussion

The implementation of the SPC chart showed the process in statistical control but lacking the ability to produce parts within specification limits (Cp<1).

An analysis of SPC charts allowed to identify changes in the mean and the variability of the process, when compared with the data obtained in the pre-production (Cpk_pre-production >1.33).)

For the analysis of the causes of process variability brainstorming sessions were held and cause-effect diagram was designed.

Through the R&R study [1] it was verified that the measuring system is unacceptable for dimensional control and thus improvement suggestions were given.

4. Conclusions

This study allowed to identify the main causes of variability in the production process of a metal part, through the application of quality tools, and to propose measures to improve process and reducing the percentage of defective parts.

Loss of process capability from the pre-production phase to the production phase can be seen as a measure of process degradation.

5. References

[1] J. M. Juran, and A.B. Godfrey, “Juran's Quality Handbook”, 5th ed., McGraw-Hill, 1999.

[2] N. Rodrigues, “Aplicação de ferramentas da Qualidade para melhoria da produção numa empresa de soluções industriais”, MSc thesis in Quality Eng and Mgmt, University of Minho, 2016.

[3] D. Montgomery, “Introduction to Statistical Quality Control”, Arizona, John Wiley & Sons, 2008.


108. Computer Aided Inspection procedures to support Smart Manufacturing of injection molded components

Michele Bici, Giovanni B. Broggiato, Francesca Campana, Alessandro Dughiero

Università degli Studi di Roma "La Sapienza", Italy

Nowadays, Reverse Engineering (RE), Computer Aided Tolerancing & Inspection (CAT&I) procedures and Product Data Management (PDM) systems can help “Smart (or Intelligent) Manufacturing”, through the planning, the automation and the post-processing of component's tolerance and quality inspection. Benefits of their adoption are enhanced predictions of the manufacturing problems and improvements of the product-process final quality. In our previous works, we discussed the integration of RE in CAT&I applied to electromechanical components made by injection molding, reporting algorithms and results that were focused onto procedures of feature recognition and measure from a point cloud.

In this work, we want to focus onto the data treatment after and before virtual measuring operations. For this reason, the paper will be organized into two macro-areas: one referred to procedures and algorithms applied before the measurement campaign, the other referred to data treatments used in “post-processing”.

The scanning and measuring operations are made through a laser scanner set on a CMM machine. In order to obtain a reliable and effective measurement campaign, pieces orientation and their layout on the reference table must be optimized, not only in the respect of the RE parameters but also considering that a large number of single very small size components must be evaluated per acquisition. In addition to the development of algorithms for layout and orientation optimization, also the development of algorithms for the laser scanner paths must be defined with the target of optimization of scan speed, keeping in mind pieces orientation and the obstruction represented by pieces in terms of visibility and scanner safety.

Passing from the CAD model to its convex hull (through a STL model), the developed algorithm researches all possible balance position for the part, and chooses the best three according to criteria as stability and visibility. Then, for each chosen position, the view perspective is reproduced, evaluating how many points are visible. We take into count the amplitude of the measurement range, occlusions and obstacles represented by the pieces themselves and the angle between the local surface’s normal and the scanner (paying attention to the differences between camera and laser).

In the second part of the paper, we analyze and discuss the automatic treatment of data after the virtual measure done with a MATLAB routine. Through these algorithms, we find plane and cylindrical local surfaces. The obtained results are compared with the nominal quotes derived from CAD model and also with ones achieved from a conventional experimental measurement campaign. An automatic procedure has been developed to resume results of the comparison in the draft file of the piece. The output of the whole process is a mix between the CAD model and a PDM, in order to obtain the direct and objective evidence of molds’ quality.

In the paper, procedures and algorithms of both sections are described, after a briefly state of the art. In the final part for each section, case studies are presented and discussed. In the last part, we present future developments and targets according to a "Smart Manufacturing" implementation.


131. Design for Inspection - Evaluating the Inspectability of Aerospace Components in the Early Stages of Design

Roland Stolt1, Fredrik Elgh1, Petter Andersson2

1Jonkoping University, Sweden, Sweden; 2GKN Aerospace AB , Flygmotorvägen 1, SE-46181 Trollhättan, Sweden

One important part of the manufacturing process of aerospace components is making inspections using Fluorescent Penetrant Inspection (FPI). This mandatory inspection represents a non-negligible part of the manufacturing and service cost. It is therefore important to make the geometry of the components suitable for inspection i.e. practicing Design for Inspection (DFI). This has been studied at an aerospace company with the aim of bringing DFI to the early stages of product development process. In this paper, a tool is proposed for the evaluation of inspectability in the early design stages. The tool is applied on CAD-models of the components automatically ranking the inspectability of design proposals using a novel inspectability index. Thus, inspectability can be considered together with other performance and manufacturing aspects forming a powerful decision support. The tool has been run and evaluated together with manufacturing staff at the aerospace company with promising results.

 
9:00am - 10:00amSES 4.5: Zero Defect Manufacturing
Session Chair: Yi-Chi Wang
Aula Q (first floor) 
 

312. Dust in lacquer, evidence of deviation of process in production lines for spray painting

Tiago Ascenção1, Teresa Pereira1,2, Francisco Silva1

1ISEP - School of Engineering, Polytechnic of Porto, Portugal; 2CIDEM – Centro de Investigação e Desenvolvimento em Engenharia Mecânica, Porto 4200-072, Portugal

This work was carried out in a multinational mobile manufacturing industry. In the painting of parts in MDF (medium density fiber cluster-medium density fibreboard) rejection values lead to a significant loss of productivity. The lines with the highest occurrence of defects are spray painting lines due its complex process. The determination of the causes for the excessive values of rejection of parts is elusive by the multiplicity of factors and parameters involved and the dispersion in the time of their application in the process, not always sufficiently or properly documented. A process analysis methodology was applied for the diagnosis of possible causes of occurrence defects. The impurities defect showed the highest rate, hence the focus of the six months’ data collection from the painting lines. Data analysis was performed using SPSS tool, to find the correlation between parameters, find optimal limits of some parameters and evidence of the influence of same factors. Meanwhile, Kaizen-Lean actions were discussed and implemented conducing to an effective reduction of existing impurities defect rate. The amount of impurities decreased nine times related with initial work values.


348. Towards robust early stage data and knowledge-based inference engine to support zero-defect strategies in manufacturing environments

Thanasis Vafeiadis1, Dimosthenis Ioannidis1, Constantinos Ziazios2, Ifigeneia Metaxa2, Dimitrios Tzovaras1

1Information Technologies Institute (ITI), CERTH Thessaloniki 57001, Greece; 2ATLANTIS Engineering SA,Thessaloniki 55535, Greece

Manufacturing represents a significant factor of EU’s GDP and its employment. Thus, the efficiency and sustainability of manufacturing processes of high-tech products along with the development of solutions for zero defect applications is more than imperative. This way European manufacturing companies will strengthen their position and keep an advantage in the highly competitive and continuous changing business environment.

Advanced Decision Support Systems (DSS) are considered as a robust technology able to provide an advantage to several manufacturing companies. As part of the Z-Fact0r EU project, an autonomous and self-adjusted early stage inference engine; namely the Early Stage-Decision Support System (ES-DSS) will be deployed. The scope is to facilitate real-time inspection, condition monitoring and control - diagnosis at the shop-floor. The objective is to use the ES-DSS to continuously mine multiple data streams and run the suitable models to monitor operations and quality performance, to classify products on the basis of quality metrics, as well to predict occurrence of defects and deviations from production and quality requirements. Appropriate PAT (Process Analytical Technologies) algorithms will be researched and selectively deployed by the ES-DSS in the use cases of the Z-Factor project to determine potentially critical process parameters. Thus, the ES-DSS inspection and control engine will be able to support zero-defect strategies in manufacturing.


356. An exploratory study on the automated sorting of commingled recyclable domestic waste

Dilan Bonello, Michael Saliba, Kenneth Camilleri

University of Malta, Malta

In material recovery facilities (MRFs) the sorting of waste is typically carried out predominantly manually. In this work, the MRF in Marsaskala, Malta is used as a case study to explore ways in which more automation can be employed to the sorting of commingled recyclable domestic waste. The work addresses first the conceptual design of the process layout and methods. This is followed by the detailed design and development of a universal gripper to replace the human sorter, aimed at removing contaminants from a stream of already sorted material, increasing the purity of the baled material and thereby increasing profits.

 
9:00am - 10:00amSES 4.6: Manufacturing Process and Technology
Session Chair: Ronny Miguel Gouveia
Aula R (first floor) 
 

175. Throughput Rate Improvement in Multiproduct Assembly Line Using Lean and Simulation Modeling and Analysis

Mahmoud Nagi, F. Frank Chen, Hung-da Wan

The University of Texas at San Antonio, United States of America

Throughput Rate Improvement in Multiproduct Assembly Line Using Lean and Simulation Modeling and Analysis

Mahmoud M Nagi, F. Frank Chen and HungDa Wan

Department of Mechanical Engineering & Center for Advanced Manufacturing and Lean Systems

The University of Texas at San Antonio, San Antonio, Texas, USA

Abstract

Variation in customer requirements is increasing day after another. It requires assembly plants to be more flexible to adopt multiple products in each assembly line. Thus, it has been a challenge to improve the throughput of multiproduct assembly lines in most cost effective manner due to the enormous complexity of the multiproduct assembly processes. Products mix and line balancing are usually the main factors contributing to the assembly line performances. Modeling and simulation of assembly lines and implementation of Lean Manufacturing and Six Sigma tools can be effective in finding insights and solutions. In this paper, we used pull simulation module to mimic an engine assembly line where 114 different products are being assembled. Line balancing, leveling and controlling the work in process (WIP) were found to be the driving elements to improve the Throughput. Developing effective design of experiments for the simulation modeling and analysis helped in validating the impact of the changes. Recommended solutions have helped the engine assembly line to increase its throughput rate by 14%.


71. The architecture of system for CNC machine tool programming

Jan Duda, Janusz Pobozniak

Cracow University of Technolgy, Poland

The goal of the paper is to present the architecture of CNC machine tool programming system based on the meta-knowledge and recognition of intermediate workpiece states. This is a Computer Aided Process Planning System (CAPP) with the functionality limited to the machining. Additionally, both the manufacturing knowledge as well ad feature recognition and processing algorithms were developed specially for the CNC machining. It was necessary to develop the module for G-code generation .

The shell expert system Exsys Professional is the main element of the proposed system. This development tool has some solutions facilitating the integration with other software packages. The knowledge is represented in the form of production rules IF... THEN...ELSE. The important function is the possibility to modify the reasoning process though the program written in the special Command Language (CL).

The manufacturing knowledge is very extensive. It is not possible to represent it using only simple rules due to the high number of such rules. The creation of consistent database will be nearly impossible. Additionally, the manufacturing knowledge has some area, which can be represented in the form of procedures. Very often they represent the basic manufacturing principles. To simplify the development of the manufacturing knowledge base and allow for the storage of procedural knowledge, the meta-knowledge in the form of hierarchical decision nets is used.

The workpiece model is created in CAD system. Manufacturing feature recognition and transformation to create the intermediate workpiece states reflecting the progress of manufacturing process were implemented in the software based on ACIS graphic kernel by Spatial Corp. The output of the manufacturing feature recognition is the feature workpiece model. This model can store the data about the manufacturing features in relational database. The data about features used in IF... THEN rules are delivered through the small programs communicating with the workpiece database and reading the output data from relational database. During process planning, the workpiece is transformed from its final state (finished workpiece) to its initial state (raw material) through the series of transformations. The transformation can result in the removal of some features (by adding material) or creation of new features, which must be recognised. The manufacturing feature recognition process is done several times. Apart from the recognition before process planning, also the recognition of workpiece intermediate states must be carried out. Such approach allows to solve the problems caused by interacting manufacturing features. According to many Authors, this is the main problem limiting the wide use of manufacturing feature technology.

The outcome of the system is G-code control program. The THEN part of some rules contains the software commands responsible for the transformation of manufacturing features. The reasoning control program written in CL language adds the beginning and end parts of the G-code program.

The goal of the proposed structure of the system is to verify the approach for CNC machine tool programming based on meta-knowledge and intermediate state recognition.


276. Manufacturing parameters optimization in a textile dyeing process

I-Hsuan Hong1, Zixin Shen1, Sheng-Chieh Chen1, Argon Chen1, Kun-Cheng Tsai2, Yu-Tong Li3

1National Taiwan University, Taiwan; 2Institute for Information Industry,11F, No. 106, Section 2, Heping E. Road, Taipei 106, Taiwan; 3Taiwan Textile Research Institute, No. 20, Kejia Rd., Hsijou Li, Douliou City, Yunlin County 64057, Taiwan

This research is to develop the dyeing parameter optimization model for functional textiles based on the analysis of relationship between the manufacturing parameters in the dyeing process and the dyeing performance. The aim of this research is to minimize the total dyeing cost including the production and energy costs with the consideration of robustness measure and dyeing performance. The first task of this research is to analyze the relationship between the dyeing parameters and dyeing performance by the Central Composite Design (CCD). The result of the CCD is the estimated response surface for the use of our second task of the dyeing parameter optimization to search for the optimal combination of dyeing parameters with a robust performance against the manufacturing variability.

 
10:00am - 10:55amKEY 3: Keynote Speech 3 (Kai CHENG)
Smart toolings and machines, and smart manufacturing
Aula Convegni (first floor) 
10:55am - 11:20amCoffee break
Gallery at first floor 
11:20am - 1:00pmSES 5.1: Data science in semiconductor manufacturing
Session Chair: Chen-Fu Chien
Aula Convegni (first floor) 
 

60. Data Mining for Yield Improvement of Photo Spacer Process in the Color Filter Manufacturing

Tsung-Lun Tsai, Chia-Yen Lee

National Cheng Kung Universisty, Taiwan

Manufacturing in TFT-LCD panel seeks a way for yield improvement and more efficient operating process. However, due to the complex manufacturing process of color filter, the panel manufacturer usually employs the design of experiments as well as engineering experience for process monitoring and quality control. This study aims to develop a three-stage data mining framework to identify the key variables significantly affecting the thickness of photo spacer process in color filter manufacturing. In the first stage, data preprocessing, we address the disorganized data with missing value and noise, and transform the dataset into a structured data frame. In the second stage, feature selection, due to the high-dimensional dataset with the small size of the observations, we develop a pre-filter module embedded with three selection methods to identify the statistically-significant variable. In the third stage, prediction and validation, two predictive models are built and the performance of the proposed models is evaluated. Finally, we report the selected variables and give feedback to the on-site engineers for the engineering validation in practice. In the validation loop, we may remove some factors, and then go back to the previous stage and repeat the circulate framework. An empirical study of a leading color filter manufacturer in Taiwan was conducted to validate the proposed framework. That result shows that the proposed framework greatly enhances the effectiveness and efficiency on identifying the key factors for yield improvement in color filter manufacturing and saves the labor resource for trouble-shooting.


62. Data Mining for Delamination Diagnosis in the Semiconductor Assembly Process

Shao-Yen Hung, Yung-Lun Lin, Chia-Yen Lee

National Cheng Kung University, Taiwan, Taiwan

The delamination in die-attach layer is a problem that results in defects of semiconductor products. There are several elements and parameters, which are difficultly observed, causing delamination during the assembly process. Thus, it’s critical to identify abnormal factors immediately for the real-time correction and improvement. This paper proposes a two-stage analysis framework to achieve two goals: identifying the key factors affecting delamination via variable selection and predicting the ratio of the delamination area in a die via the prediction models. In the first stage, due to the high-dimensional problem in the dataset, we apply L1 regularized regression (i.e. LASSO) and stepwise regression to extract critical variables that show significantly influence on delamination. In the second stage, we build up three models with different geometric illustrations─ backpropagation network (BPN), support vector regression (SVR) and partial least squares (PLS), to predict the delamination ratio in a die. An empirical study of a leading semiconductor assembly company in Taiwan is conducted to validate the proposed framework. The results show that some variables we finally identify are confirmed by engineer test to present potential physical meanings, and the BPN model provides better predicting accuracy. Further, we investigate the imbalance between false positive rate and false negative rate after the quality classification, and apply the gradient boosting machine (GBM) to improve the imbalance problem and give some insights for supporting practical decision.


188. Multi-Pass Lot Scheduling Algorithm for Maximizing Throughputs at Semiconductor Final Test Facilities

Sang Won Yoon, Young Min Joung, Tian He, Ravi Vancheeswaran, Cecille Abela, Herwina Richelle Andres

State University of New York at Binghamton, United States of America

This research proposes a multi-pass oriented scheduling heuristic algorithm to determine the test schedules, machine setups, and job assignments for multi-pass lots at a semiconductor final test facility with an objective of maximizing the lot throughput. The proposed algorithm dispatches a group of selected lots and all their passes at a time. The performance of the algorithm is evaluated using the subset data from industry. The results indicate that the proposed heuristic can improve the rate of weekly lot throughput by 9.46% and 7.76% on average compared to the results obtained from the single-pass oriented and the genetic algorithm, respectively.


242. Tool planning model with calibration in semiconductor equipment manufacturer

YiHsuan Yang, Chen-Yang Cheng

National Taipei University of Technology, Taiwan

This research is motivated by issues confront with a large manufacturer of semiconductor equipment. In producing semiconductor equipment, when the number of tool sent back to the supplier to be calibrated is different greatly in month. This will result in production tool shortage problem. In order to avoid the shortage problem at the time of production, the number of tools to be calibrated each month should be taken into consideration when scheduling the tool. Therefore, this research is to develop a tool planning model with tool calibration quantity balance monthly. This model balances the calibrated tool quantity every month.


294. Anomaly Detection Approaches for Semiconductor Manufacturing

Gian Antonio Susto, Matteo Terzi, Alessandro Beghi

University of Padova, Italy

Smart production monitoring is a crucial activity in advanced manufacturing for quality, control and maintenance purposes. Advanced Monitoring Systems (AMSs) aim to detect anomalies and trends; anomalies are data patterns that have different data characteristics from normal instances, while trends are tendencies of production to move in a particular direction over time.

Instruments to implement efficient AMSs are provided by Machine Learning (ML). ML approaches have proliferated in recent years Advanced Process Control (APC) solutions for Semiconductor Manufacturing, thanks to the algorithmic advancements in the field and the increased computational and storage capabilities in the IT architecture of the Fabs; ML-based approaches have been used for Virtual Metrology, Predictive Maintenance and Fault Detection applications. In this work we compare state-of-the-art ML approaches (ABOD, LOF, OnlinePCA and HOTSAX) to detect outliers and events in high-dimensional monitoring problems.

The compared anomaly detection strategies have been tested on a real industrial dataset related to a Semiconductor Manufacturing Etching process; the data available consists of 1970 wafers belonging to a set of 282 (not complete) lots, for which Optical Emission Spectrometry (OES) are available; the process in question is plasma etching, for which OES data represents a non-costly and informative source of information from a chemical point of view. The dataset also includes information on another important quantity, the Etching Rate, that is the ratio between the depth of the created trench and the time taken to perform the ‘excavation’. The Etch Rate is used in this work as a quality indicator for the produced wafers: outliers or changes seen in the Etch Rate can be considered as anomalies or changes in the production. Unfortunately the Etch Rate is costly to compute in production and in some production settings is not available for most produced wafers; this scenario underlines the importance of an AMS that is able to infer anomalous situations from different data sources, like OES data.

 
11:20am - 1:00pmSES 5.2: Production Planning and Scheduling
Session Chair: Rita Gamberini
Aula N (first floor) 
 

132. A New Performance Indicator of Material Flow for Production Systems

Chi-Shuan Liu1, Luo-Yan Lin1, Ming-Chih Chen2, Horng-Chyi Horng1

1Chaoyang University of Technology, Taiwan; 2Graduate Institute of Business Adminstration, Fu Jen Catholic University, 510 Zhongzheng Rd., Xinzhuang, New Taipei City 24205, Taiwan

This research develops a new performance indicator for material flow effectiveness in production systems. To develop the so-called flow value, the first step is performing work sampling on Work in Processes (WIP) of the current production. These WIPs are then given different weightings in the calculations of flow value, based on their job types, locations in the system, and so on. This flow value can represent the smoothness of material flow in a production system, thus can be used as real time indicator to instantly reveal the performance of a production system. A simulation study on a machining equipment manufacturing company in Taiwan validates the usefulness of using flow value as an indicator of material flow performance. This flow value is also capable of revealing areas where improvement can be made to effectively improve total system’s performance in terms of material flow.


251. A framework for task sequencing for redundant robotic remote laser processing equipment based on redundancy space sampling

Sigurd Lazic VIllumsen, Morten Kristiansen

Aalborg Universitet, Denmark

This paper presents a framework for task sequencing of redundant remote laser processing equipment. The task sequencing algorithm is based on generating sets of robot configuration samples on all processing contours. The sequencing is done by using a solver for the equality constrained generalized traveling salesman problem (E- GTSP) to find the shortest path between these sets, while taking process constraints, robot redundancy and cluster connectivity into consideration. The algorithm was implemented in Matlab with interfaces to the robot simulation program V-rep and the GLKH E-GTSP solver. A test was carried out with 38 contours on a work piece with a set of angled plateaus.


382. Balanced Adaptive Tabu Search Algorithm to Optimize Dual-Gantry Pick-and-Place Assembly

Debiao Li1, Rui Qiang1, Sang Won Yoon2

1Fuzhou Uuniversity, China, People's Republic of; 2Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Binghamton, NY, 13902, US

This paper presents an optimization study of dual-gantry high-speed rotary-type pick-and-place surface mount device (SMD) machine. In the dual-gantry SMD machine, there are two feeder bases and gantry heads, such that two placement heads can pick-and-place synchronously in one PCB, which has an advantage in assembly PCB with more component types. The dual-gantry optimization problem is decomposed into nozzle arrangement, feeder assignment, pick-and-place sequence, component allocation, and gantry schedule problems. To balance the workload between gantries and reduce the wait time in the gantry's synchronous movement, a balanced adaptive tabu search (BATS) algorithm are proposed. Based on the 16 industrial data tests, the proposed algorithm yields a 7.04% improvement on average compared to the industrial package.


214. Stencil printing optimization using a hybrid of support vector regression and mixed-integer linear programming

Nourma Khader1, Sang Won Yoon1, Debiao Li2

1State University of New York at Binghamton, United States of America; 2School of Economics and Management, Fuzhou University, Fuzhou, China

This research proposes an optimization approach to enhance the stencil printing process (SPP) in surface mount printed circuit board (PCB) assembly. Stencil printing behavior is affected by many variables including stencil design, solder paste composition, squeegee speed and pressure, and other environmental conditions. In this research, support vector regression (SVR) model is trained to capture the complex relationships among these variables, based on historical data. A mixed-integer linear programming (MILP) model is proposed to minimize the total absolute predicted deviation of average volume transfer from target. The optimal printing settings are retrieved for different sample problems with low computational cost.


376. ON THE ANALYSIS OF EFFECTIVENESS IN A MANUFACTURING CELL: A CRITICAL IMPLEMENTATION OF EXISTING APPROACHES

Rita Gamberini, Luca Galloni, Francesco Lolli, Bianca Rimini

University of Modena and Reggio Emilia, Italy

OEE (Overall Equipment Effectiveness) is a widely used indicator in the evaluation of effectiveness of manufacturing systems. However, several authors published alternative approaches for its computation, complicating the implementation step for practitioners. This study analyses the literature regarding OEE, selects four main methodologies for its evaluation and examines the underlying differences between them. A real life case study is analysed to illustrate problems arising during data collection and the differences in results obtained, together with traceable conclusions for improving the performance of production systems, both in traditional and in innovative industrial plants, following Industry 4.0 principles.

 
11:20am - 1:00pmSES 5.3: Collaborative Robotics in Smart Manufacturing
Session Chair: Pedro Neto
Aula O (first floor) 
 

87. Safeguarding and supporting future manufacturing processes by a projection- and camera-based technology

Christian Vogel, Christoph Walter, Norbert Elkmann

Fraunhofer-Institut für Fabrikbetrieb und -automatisierung, Germany

The International Federation of Robotics (IFR) forecasts that the number of newly installed industrial robots will reach 1.4 million by 2019. With this increase of robots in industrial automation, the demands for human-robot cooperative workplaces are also set to rise. Workplaces that allow concurrent work of humans and robots in a shared environment require that the human is safeguarded at all times. But in future industrial manufacturing the hard-safety aspect won’t be the only requirement to such cooperative workplaces. Soft-safety, interaction functionalities and worker assistance will contribute to an overall flexible and innovative human-robot workplace. In this article we propose a trendsetting technology that can fulfil all of the aforementioned requirements to future workplaces featuring human-robot cooperation. This technology, which is based on projection and camera techniques, was applied to an industrial manufacturing process to enable safe and interactive cooperation between humans and robots. A demonstrator as well as the single functionalities and benefits will be presented in this contribution in detail.

The projection- and camera-based technology is capable of establishing safety zones of arbitrary shape, size and position directly into the shared workspace of human and robot. By connecting this safety system to the robot’s controller, the safety zones can be dynamically generated on basis of the robot’s joint angles and velocities. Here, the approach formula described in ISO/TS 15066 is used to calculate the safety distances that will form a minimal safety hull enclosing the robot at any time. The safety system incorporates the calculated safety hull to generate and emit a border in the form of a line (i.e. the border of the safety zone) that separates the human and robot. If this projected line is disrupted by an object such as a human’s hand or fingers, the surrounding cameras recognize this safety zone violation robustly. A safety zone violation results in the reduction of the robot’s speed or even an immediate stop. From the perspective of the human co-worker, it is generally advantageous to be aware of the current safety zone, giving them the possibility of actively avoid safety violations. This will lead to an improved availability of the robot and the entire system. Visualizing additional symbols to represent intended robot movements will further enhance the user acceptance.

The main benefits of this projection- and camera-based approach for workspace surveillance are the minimized (none-) dependence on environmental light conditions, intrinsic safety, high potential for safety certification and overall valuable functionalities. Here, the capability of providing virtual interactive buttons that allow the control of robot (start/ pause motion), system (choose/ manage task) and process (confirm production step) is very useful. Besides interaction, the system also offers the visualization of safety-, robot- or process-relevant information directly into the shared workspace supporting the human in work, configuration, and even failure diagnosis.

The interaction and visualization capabilities as well as the safe workspace surveillance provided by this projection- and camera-based technology will be presented on basis of an industrial demonstrator featuring a screwing application.


88. Safeguarding collaborative mobile manipulators - Evaluation of the VALERI workspace monitoring system

José Saenz, Christian Vogel, Felix Penzlin, Norbert Elkmann

Fraunhofer-Institut für Fabrikbetrieb und -automatisierung, Germany

The project VALERI focused on the validation of mobile manipulators for use in aerospace production. This paper focuses on the development and application of a 2 ½ D workspace monitoring system for safeguarding tools when working in close proximity to human operators. Following a brief overview of the set-up and operational principles of the workspace monitoring system, we will detail the assumptions made in the risk assessment and the methods used to minimize the size of the necessary protective distance. An experimental validation and an outlook for future work will also be described in this contribution.


160. A Skill-based Robot Co-Worker for Industrial Maintenance Tasks

Paul Jakob Koch, Marike Koch van Amstel, Partycja Dębska, Moritz Alexander Thormann, Adrian Johannes Tetzlaff, Simon Bøgh, Dimitrios Chrysostomou

Aalborg university, Denmark

This paper investigates the concept of a sensor-based robot co-worker working in flexible industrial environments together with and alongside human operators. In this particular work, a realisation of a robot co-worker scenario is developed in order to demonstrate the implementation of a robot co-worker from the starting point of an autonomous industrial mobile manipulator. The cobot is applied on the industrially relevant task of screwing by the use of a skill-based approach. The technical work on the human-robot interface and the screwing skill is described.


182. Minimum distance calculation for safe human robot interaction

Mohammad Safeea, Nuno Mendes, Pedro Neto

University of Coimbra, Portugal

The ability of efficient and fast calculation of the minimum distance between humans and robots is vitally important for realizing a safe human robot interaction (HRI), where robots and human co-workers share the same workspace. The minimum distance is the main input for most of collision avoidance methods, HRI, robot decision making, as well as robot navigation. In this study it is presented a novel methodology to analytically compute of the minimum distance between cylindrical primitives with spherical ends. Such primitives are very important since that there geometrical shape is suitable for representing the co-worker and the robots structures. The computational cost of the minimum distance between n cylinders is of order 〖O(n〗^2). In this study QR factorization is proposed to achieve the computational efficiency in calculating the minimum distance mutually between each pair of cylinders. Experimental tests demonstrated the effectiveness of the proposed approach.


209. Interactive simulation of human-robot collaboration using a force feedback device

Uwe Dombrowski1, Tobias Stefanak1, Jerome Perret2

1TU Braunschweig, Germany; 2Haption Gmbh, Aachen, Germany

The role of robots in manufacturing processes is undergoing a revolution. Tremendous gains in productivity and flexibility can be achieved by removing the fences and letting humans and robots work together in the same workspace. However, new risks have to be addressed, and new means of optimization are needed. Through the use of collaborative robotic systems in final assembly, also the demands on the methods and tools of the digital factory, especially the simulation, are increasing.

In this paper, we demonstrate the use of interactive simulation as a tool for workcell validation and optimization. The proposed technique combines real-time physics simulation and motion capturing systems in order to immerse the design engineer or production planner inside a responsive virtual model of the factory. The user can interact with components and tools, as well as with the robots performing their assigned tasks, including collaborative steps. The handguiding function of sensitive lightweight robots can be simulated using force feedback devices. For example, it is possible to experience the new impedance mode of a KUKA LBR iiwa in an intuitive and tangible, but completely simulated way. Future application scenarios can be directly tested in the assembly process simulation. Thanks to this first-person 3D experience, a better understanding of the risks, complexity and potential improvements can be reached. With this knowledge, it is possible in early planning stages to define the first working and protection areas for safety programming. These are necessary for the human-robot collaboration to be safe. Virtual auxiliary geometries in the form of combined spheres represent the used robot tool in safety control. The radii of the different spheres can be determined in relation to the size and position of the previously defined areas. In this way, in addition to safety, the process reliability can be optimized in the simulation, too.

Referring to the structure of this paper, first the requirements of the interactive simulation are defined. Then the state-of-the-art of the domain is reviewed. The paper describes the implementation and gives some figures about the performances achieved. Then the method is illustrated on a real-case scenario in the automotive industry and some key results are given. Finally, the paper shows how the same approach can be beneficial for other aspects of advanced manufacturing, such as ergonomics and human factors, intuitive robot programming, and virtual training.

 
11:20am - 1:00pmSES 5.4: Digital Product and Process Development
Session Chair: Marco Mandolini
Aula P (first floor) 
 

193. Multi-criteria classification for spare parts management: a case study

Isabel Lopes, Catarina Teixeira, Manuel Figueiredo

University of Minho, Portugal

Inventory management of spare parts for production equipment is a process that can affect the performance of maintenance management and therefore productivity. A need for spare parts arises whenever a component fails or requires preventive replacement, i.e., to perform a preventive or corrective maintenance action. Holding spare parts may involve, in case of expensive and rarely used parts, high inventory holding costs. On the other hand, the unavailability of a spare part may lead to a long and unproductive downtime of the production equipment. Therefore, the right balance between the two sides needs to be found.

Spare parts stock management is quite specific compared to stock management of production materials and parts, because parts can be expensive and demand is highly erratic and intermittent, yet their shortage costs can be very large. Therefore, appropriate strategies in procurement, stocking and supply play a key role in spare parts management. Including spare parts management in computerized maintenance management systems (CMMS) is advantageous for the integration of logistics and maintenance perspectives.

To define a suitable stock management system, a spare parts classification is recommended due to the different characteristics of parts. This classification is important to determine service requirements for different spare parts classes, for forecasting demand and stock control decisions.

This paper presents an ongoing project aiming to develop a spare parts classification for integration in a CMMS of a manufacturing company. The classification methodology should be able to define groups for which a stock management policy will be associated. The selection of the most appropriate criteria and the allocation of weights is essential in this process. Initially, a classification will be carried out to identify the necessity and importance of spare parts for maintenance. After that, a multi-criteria classification, including the previous maintenance classification, will be used for defining the groups.

For the maintenance classification, a multi-criteria methodology will be used to assign parts to three levels. The result of the maintenance classification will be used as criteria in the second classification along with inventory management related criteria which should allow finding suitable policies. This methodology was applied to a sample of spare parts and the results were analyzed.


342. Analysis of the requirements of an early life-cycle cost estimation tool: an industrial survey

Andrea Savoretti1, Marco Mandolini1, Roberto Raffaeli2, Michele Germani1

1Università Politecnica delle Marche, Italy; 2Faculty of Engineering, Università degli Studi eCampus, Via Isimbardi, 10, Novedrate, 22060, Italy

Cost estimation is a critical issue for many companies concerning both offers generation and company strategic evaluations. In this paper, a framework for early cost estimation has been proposed to some firms for an assessment of its main features. The aim of the industrial survey is to promote a discussion on the needs and the expectations regarding cost estimation in order to obtain feedbacks to be addresses in the implementation of a software tool. Gather data has led to a ranking of the main characteristics the tool should have.

© 2017 The Authors. Published by Elsevier B.V.

Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing.

Keywords: Knowledge-based engineering ; Design to Cost ; Product configuration ; Early cost estimation ; CAD ; PLM


53. A Hybrid Transport Concept for the Material Supply of a Modular Manufacturing Environment

Michael Scholz, Jörg Franke, Mario Serno, Peter Schuderer

Institute of Factory Automation and Production Systems, Germany

Tugger trains are an energy-efficient possibility to handle intralogistics material supply due to the bundling of purchasing volumes. The technologies of Industry 4.0 allow the horizontal integration of these systems to manufacturing machines in the up- and downstream which leads to a data processing in real time. Related to the material supply, this method means, that the supply system detects immediately on which position material is required. Due to its decentralized pathing algorithms an energy-efficient tour of the autonomous tugger train is planned and executed. However, against the background of current developments in the area of manufacturing organisation, the tugger train principle reaches its limits. Today’s research projects, like ARENA 2036 or Smart Face, propose modular manufacturing environment, which could adept itself to current customer demand and make autonomous manufacturing decisions.

The spatial nearness of these units and the necessity of a high-frequented and small-scaled supply lead to the application of small-scaled autonomous transport entities for the material supply of such a manufacturing surrounding.

Versatile autonomous vehicles have advantages to tugger trains in these manufacturing environment, because of their size, flexibility and the energy efficient transportation of small transport volumes. The main disadvantage is the increasing of the intralogistics traffic within the operation of small scaled vehicles in a swarm. The remedy could be a high-level instance which executes the route design of the small-scaled transportation unities.

However, this approach disagrees with the demand of a freely meshed, scalable and autonomous material handling. Therefore, the approach of this paper connects the advantages of small-scaled transportation entities with the advantages of self-pathing and flexible tugger train system. The main paths are operated by the autonomous tugger trains which carry the small-scaled entities to defined operation areas. Finally, the small-scaled transportation entities are the bridge to the "last meter" of the transportation task. Therefore, the transportation quantity is reduced on the one hand and, on the other hand, the high flexibility of the small-scaled transport entities is used.


369. Extension of STEP-NC data structure to represent manufacturing process structure in CAPP system

Janusz Pobozniak1, Sergiusz Sobieski2

1Cracow University of Technolgy, Poland; 2TIZ Implements Sp. z .o.o., ul. Kocjana 1/U4, 01-473 Warsaw, Poland

STEP-NC is a new standard for Computer Numerical Control (CNC) machine tool programming. It contains many elaborated data models for milling and turning, including the representation of parameters and geometry of machining features. The paper presents the use of STEP-NC data model for CAPP system under the development. The structure of manufacturing process was analyzed and the method to represent it using STEP-NC entities was proposed. New entities were added to store the information required by CAPP system, including the manufacturing process other than machining. Express-G data modelling language was used for this purpose.

© 2017 The Authors. Published by Elsevier B.V.

Peer-review under responsibility ofthe scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing.

Keywords: CAPP, Computer Aided Process Planning; CNC, STEP-NC, ISO 10649


266. Weldability Knowledge Visualization of Resistance Spot Welded Assembly Design

Md Tarique Hasan Khan1, Fahim Ahmed2, Kyoung-Yun Kim3

1Wayne State University, United States of America; 2Ph.D. Student, Industrial and Systems Engineering Deaprtment, Wayne State University, Detroit 48202, USA; 3Associate Professor, Industrial and Systems Engineering Deaprtment, Wayne State University, Detroit 48202, USA

This paper presents a Resistance Spot Welding (RSW) weldability knowledge visualization framework. To realize this visualization framework, real industry RSW quality datasets are analyzed using data mining algorithms and weldability decision rules are extracted. Then, an RSW ontology is employed to build a shareable RSW weldability knowledge model from the extracted decision rules, by converting into Semantic Web Rule Language rules. To visualize the weldment design integrated with the weldability knowledge, the RSW ontology data is mapped and integrated with X3DOM models and then X3DOM models are utilized for the visualization of welded assembly design. Finally, the visualization framework is implemented and demonstrated with a case study.

© 2017 The Authors. Published by Elsevier B.V.

Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing.

Keywords: RSW; welded assembly design; ontology; visualization; OWL; SWRL; X3DOM

 
11:20am - 1:00pmSES 5.5: Sustainable Manufacturing
Session Chair: Munir Ahmad
Aula Q (first floor) 
 

21. Key Performance Indicators for Sustainable production Evaluation in Oil and gas sector

Redha Mahoumd Elhuni1, Munir Ahmad2

1Libyan Petroleum Istitue, Libya; 2School of science & engineering, Teesside University, Middlesbrough, TS1 3BA UK

The oil and gas sector has grown significantly over last decade and have a significant impact on sustainable development, making it important for the sector to implement serious changes in the way it does business. Oil and gas operations involve both upstream activities, including all processes before the raw material is refined; exploration, drilling, extraction, storage, shipping, etc., and downstream activities, which involves the refining, selling and distribution of the product. Due to the nature of these activities which cause high risks, companies work continuously to reduce the significance of their adverse impacts on the environment and people. Thus, evaluating the sustainable production in this sector is become a necessity. This paper proposes a set of Key Performance Indicators (KPIs) for evaluating the sustainable production believed to be appropriate to the oil and gas sector based on the triple bottom line of sustainability. The Analytical Hierarchy Process (AHP) method is applied to prioritize the performance indicators by summarizing the opinions of experts. It is hoped that the proposed KPIs enables and assists this sector to achieve the higher performance in sustainable production and so as to ensures business sustainability.


164. Use of Design Structure Matrix for Analysis of Critical Barriers in Implementing Eco-design Initiatives in Pulp and Paper Industry

Shqipe Buzuku, Andrzej Kraslawski

Lappeenranta University of Technology, Finland

Eco-design initiatives are gaining importance due to changing environmental conditions and the industry is developing different solutions. The purpose of this paper is the identification and evaluation of barriers related to the implementation of eco-design initiatives in pulp and paper industry. This study identifies the key barriers through literature research and provides information flow dependencies using design structure matrix through a case study of a company in Finland. This method differs from traditional management tools because it focuses on representing information flow rather than workflow. The findings provide policy recommendations to policy makers for managing eco-design implementation.


58. Using Indicators to Measure Sustainable Resource Management at a Company level – polish case study in recycling sector

Monika Kosacka, Karolina Werner-Lewandowska

Poznan Univeristy of Technology, Poland

The growing interest in sustainability worldwide resulted in a parallel growth in works related to the specified topic. The greatest challenge is to translate the theoretical goal of sustainable development into practical usage at different levels of application, including the company level.

In the paper authors are focused on application of the sustainability at the company level. It was assumed that sustainability is not a possibility of building company’s competitiveness but it becomes a requirement. Moreover sustainability should be managed. Consequently, to manage something it requires measurement. Taking that into consideration authors define in the paper a concept of the sustainable resource management (SRM) as translation of the sustainability at the company level with the use of resource based view theory. On the basis of the conducted literature research it was noted that there is lack of method for the SRM using indicators.

In the study, there is presented a method of indicators determination for SRM, recommended for the companies from car recycling sector in Poland, which are mainly representing SME’s.

Authors state that indicators for measuring SRM should be dedicated to the characteristic of the company determined by the size, type and sector.

A case study at a polish car recycling company has been performed to prepare the set of indicators according to the described method.


215. Measuring Business Sustainability Maturity-Levels and Best Practices

Itzel Donaji Meza-Ruiz1, Luis Rocha-Lona1, Maria Del Rocio Soto-Flores1, Jose Arturo Garza-Reyes2, Gabriella Citlali López-Torres3, Vikas Kumar4

1Instituto Politécnico Nacional, ESCA Santo Tomás, Mexico City, 11340, México; 2Derby Business School, The University of Derby, Derby, DE22 1GB, UK; 3Bristol Business School, University of the West of England, Bristol, BS16 1QY, UK; 4Centro de Ciencias Económicas y Administrativas, Universidad Autónoma de Aguascalientes, Ciudad Universitaria Aguascalientes, 20131, Mexico

There has been an increasing interest in corporate sustainability (CS) and how companies should strive for it in order to satisfy stakeholders’ demands concerning social, economic, and environmental impacts. The purpose of this paper was to identify the best sustainability practices and the sustainability maturity levels that allow manufacturing and service companies to contribute to sustainable development in the long run. Based on a qualitative approach, a comparative study of five large companies was deployed in order to determine their sustainability maturity levels and best practices. The research method consisted of a critical review of the literature and category analysis concerning corporate sustainability trends and some of the best well-known performance frameworks such as the Global Reporting Initiative (GRI), business excellence models (BEMs), and international standards. The main findings reveal that companies’ sustainability maturity levels range from satisfactory to sophisticated in several sustainability aspects. Best sustainability practices found in this sample include the use of certifications such as ISO 9000, ISO 14001, GRI, and CSR, among others, combined with the systematic use of BEMs over many years. Finally, several key processes such as self-assessment, benchmarking, corporate reporting, strategic planning, and systematic training were found to be significant in helping manufacturing and service organisations achieve their business sustainability objectives.


325. Understanding the Relationship between Stakeholder Pressure and Sustainability Performance in Manufacturing Firms in Pakistan

Usama Awan, Andrzej Kraslawski, Janne Huiskonen

Lappeenranta University of Technology, Finland

Sustainable supply chain practices has been acknowledged among the supply chain scholars due to its importance as a key to promote sustainability. The aim of this paper is to examine the relationship between stakeholder pressure and adoption of sustainable supply chain practices and impact on sustainability performance. The study draws on stakeholder theory and the resource-based view of the firm, data was collected through survey methodology from 272 manufacturing firms in Pakistan and hypothesis tested using structural equation modelling (SEM). The sustainability performance is combination of environmental and social performance.The conclusion signifies the important role that SSCP can play in achieving the social and environmental performance of the manufacturing firms. Thus supply chain managers will perceive benefits to significant involve buyers in collaborative social and environmental practices. This study suggest the policy implications and recommendations to the practitioners as how to improve the social performance in manufacturing firms in context with the emerging economies.

 
11:20am - 1:00pmSES 5.6: Smart Factories and Industrial IoT
Session Chair: Dusan Sormaz
Aula R (first floor) 
 

79. Modelling supply chain performance

Paul-Eric Dossou, Meriem Nachidi

Icam, France

Due to globalisation and economic crisis in Europe, the situation of industrial companies is decreasing. European countries have to think about how to reorganise themselves in order to increase their performance. Recently, many ideas and strategies have been proposed to improve working life and production systems. Indeed, many European countries nowadays adopt industry 4.0 and supply chain 4.0. Enterprise modelling methodologies define enterprise as a system, which can integrate new technologies, Internet of things, automation, robotics and so on.

GRAI methodology is used for enterprise modelling and its tool GRAIMOD is being developed for supporting the methodology [Dossou, 2015]. For elaborating GRAIMOD, new concepts and formalisms are defined. For instance, a knowledge representation is defined as rules for analysing and designing enterprises, old cases for elaborating solutions by using CBR (Case Based Reasoning) and reference models are done according to activity domains for facilitating design of new solutions. Criteria and a dashboard are defined for measuring supply chain performance (existing system and future system).

Thus, the state of a company can be determined by a set of mathematical equations that connects their inputs and outputs. Classical modelling approaches can be used to improve performance criteria including quality, cost, lead-time, carbon management, energy efficiency, and social, societal and environmental.

This paper deals with modelling supply chain performance taking into account the performance criteria. A zoom is made on quality and lead-time criteria for illustrating the developed concepts.

Then a real application on a company is given to validate concepts elaborated. A comparison is made with the real use.


159. Location Independent Manufacturing – Software solution for supply chain

Merja Peltokoski, Jarno Volotinen, Mika Lohtander

Lappeenranta University of Technology, Finland

All over the world the companies are trying to concentrate on producing environmentally friendly products. Global megatrends are going towards ageing, individualism, globalization, urbanization, and sustainability. To reduce the waste and emissions environmental impact has to be take into account. Ecological behavior reflects to produce recyclable products and great production that is in its entirety environmental friendly. Not only the production has to be ecological, also the raw materials has to be ecological, logistic emissions has to reduce and ethical decisions has to be made. Globalization itself is forcing companies to be competitive and in the future the globalization will be key enabler of economic growth.

To answer the challenges of globalization, sustainability and the upcoming megatrends, the key solution is going to be Location Independent Manufacturing (LIM) concept. The LIM concept is new manufacturing philosophy and it has been get attention in Finnish SMEs’, but it hasn’t been fully implemented by any company. LIM is not only solution for faster and more sustainable production but it also cutting down emissions in transportation and provide new markets for SME’s far away from consumption centers.

To reach these previous mentioned goals the new manufacturing operation model is needed. New developed operation model is based on open information from internet. Software is utilize open data like custom costs, custom’s commodity codes, corporation taxes and environmental laws. Software could be used as a comparison or an optimization tool. In this research the software is aim to Finnish SMEs, where the projects and products are changing all the times. With the help of this LIM software, it is possible to compare the operation models on site: how to obtain cheapest end product or what the actual cost for delivery are, when the materials or semi-final products are coming from different subcontractors. This LIM software is also comparing taxations, logistic costs, and company’s production model in destination country. Remarkable savings could be achieve if proposed software is used.


310. An integrated logistics concept for a modular assembly system

Wolfgang Kern1,2, Hannes Lämmermann2, Thomas Bauernhansl1,3

1GSaME Graduate School of Excellence advanced Manufacturing Engineering, University of Stuttgart, 70569 Stuttgart, Germany; 2Audi AG, 85045 Ingolstadt, Germany; 3Fraunhofer Institute for Manufacturing Engineering and Automation IPA, 70569 Stuttgart, Germany

The trend towards product differentiation in the automotive industry increases the complexity in its assembly and logistics. Hence, more flexible systems are required and already in development. Based on the requirements of a modular assembly system, an adapted production logistics concept with decentralized logistics areas at each workstation is described in this paper. The modular system without a fixed sequence of products is enabled by five types of material supply differentiated in the integrated logistics concept. As a result, an effective assembly of present and future automobiles can be ensured despite their variety.


365. Modeling a Leagility Index for Supply Chain Sustenance

Arnab Banerjee1, Farnaz Ganjeizadeh2

1CSUeastbay.edu, United States of America; 2Professor, Califirnia State University, East Bay, USA

For a sustainable Leagile Supply chain it is important to measure and optimize the leagility. Governance of leagility sustenance needs the supply chain performance to be measured and optimized through a means termed by us as ‘Leagility Index’. The paper details the modelling approach for calculating leagility index. The calculation is proposed via conjoint analysis. The sustenance model further optimizes the supply chain using Simulated Annealing (SA) in a practical process adoption scheme. The index acts as a guide for sustenance model of supply chain.


37. The Impact of Supply Chain Integration on Performance: Evidence from the UK Food Sector

Vikas Kumar, Esinaulo Nwakama Chibuzo, Jose Arturo Garza-Reyes, Archana Kumari, Luis Roch-Lona, Gabriela Citlalli Lopez-Torres

University of the West of England, United Kingdom

Supply chain Integration has emerged as a major field of interest over the years that involve the strategic alignment of functions and processes within an organization. However, there have been major debates regarding the true design of the kinds of integration that would lead to performance of supply chains. This study develops a conceptual framework from the literature and defines four constructs of integration (customer, supplier, internal, and information integration) to see how this would lead to improved supply chain performance (such as production flexibility, inventory turns, order fulfillment rate, total logistics costs, and operational performance).

 
1:00pm - 1:50pmLunch break
Courtyard at ground floor 
1:50pm - 3:10pmSES 6.1: Collaborative Robotics in Smart Manufacturing
Session Chair: Pedro Neto
Aula Convegni (first floor) 
 

183. Hand/arm gesture segmentation by motion using IMU and EMG sensing

João Lopes, Miguel Simão, Nuno Marques Mendes, Mohammad Safeea, José Afonso, Pedro Neto

University of Coimbra, Portugal

Gesture recognition is more reliable with a proper motion segmentation process. In this context we can distinguish if gesture patterns are static or dynamic. This study proposes a gesture segmentation method to distinguish dynamic from static gestures, using (Inertial Measurement Units) IMU and Electromyography (EMG) sensors. The performance of the sensors, individually as well as their combination, was evaluated by different users. It was concluded that when considering gestures which only contain arm movement, the lowest error obtained was by the IMU. However, as expected, when considering gestures which have only hand motion, the combination of the 2 sensors achieved the best performance. Results of the sensor fusion modality varied greatly depending on user. The application of different filtering method to the EMG data as a solution to the limb position resulted in a significative reduction of the error.


257. Teaching Assembly by Demonstration using Advanced Human Robot Interaction and a Knowledge Integration Framework

Mathias Haage1, Grigoris Piperagkas2, Christos Papadopoulos2, Ioannis Mariolis2, Jacek Malec1, Yasemin Bekiroglu3, Mikael Hedelind3,4, Dimitrios Tzovaras2

1Lund University, Sweden; 2Centre of Research & Technology – Hellas, 6th km Charilaou - Thermi, 57001, Thessaloniki, Greece; 3ABB AB Corporate Research, Sweden,; 4VINNOVA, Sweden

Industrial robots have been successfully used in manufacturing by reducing production cost and eliminating unsound manual work. However, the use of industrial robots in assembly applications still suffers from complex, time-consuming programming and the need for dedicated hardware. In this work a novel system is presented that proposes the use of a teaching by demonstration methodology that would significantly reduce the time and required expertise to setup a robotized assembly station. The teaching by demonstration paradigm has been sought after in the robotics community for a long time, however, it is now believed to be an achievable approach due to recent developments in perception and cognition systems. Three key components within the proposed system are described; a portable human robot interaction interface, a perception module and a knowledge integration framework. An experimental setup and a teaching-by-demonstration experiment are presented utilizing the described components. The setup targets assembly of small parts, e.g. cell phone components, using a collaborative industrial robot, the ABB YuMi. The experiment targets the insertion of one mobile phone component into another through a folding movement, taught by human demonstration. The human instructor is guided by the HRI interface on how to teach the robotic system a new assembly. The experiment considers a single two-part assembly in each demonstration. The parts are placed in front of the system’s camera and the instructor performs the assembly of the parts. Utilizing image analysis and machine learning methods, the perception module uses the demonstration data to track the pose of the parts throughout the assembly and select basic snapshots of the demonstration called key-frames. The key-frames contain visual information of the scene, the extracted information by the perception module, and semantic information that can be edited by the user through HRI. The user can also inspect the automatically extracted key-frames, in order to add or remove any from the extracted list. Once the list with the semantically annotated key-frames is created, it is provided by the system to the Assembly Program Generator module, which generates a new assembly program for the robot, utilizing a Knowledge Integration Framework. Automatic generation of the assembly program is based on the semantic information of the key-frames, with each semantic annotation corresponding to a state of a Sequential Function Chart (SFC), whereas the order of the key-frames in the list defines also the order of the state sequence. Transitions between states are predefined based on the type of the assembly and the skills the system has already acquired. The folding insertion movement is characterized by a SFC sequence including the sub-states: grasping, picking, aligning, establishing contact, and folding. Qualitative evaluation indicates the usefulness of the presented approach. Planned efforts include the use of physical Human Robot Interaction during execution of the assembly in order to fine-tune the demonstrated operation using a learning by doing approach.


81. Walk-through programming for industrial applications

Federica Ferraguti1, Chiara Talignani Landi1, Cristian Secchi1, Cesare Fantuzzi1, Marco Nolli2, Manuel Pesamosca2

1Università di Modena e Reggio Emilia, Italy; 2Gaiotto Automation, via Toscana 1, 29122 Piacenza, Italy

Collaboration between humans and robots is increasingly desired in several application domains, including the manufacturing domain. The paper describes a software control architecture for industrial robotic applications allowing human-robot cooperation during the programming phase of a robotic task. The control architecture is based on admittance control and tool dynamics compensation for implementing walk-through programming and manual guidance. Further steps to integrate this system on a real industrial setup include the robot kinematics and a socket communication that sends a binary file to the robot.


274. Assisted Hardware Selection for Industrial Collaborative Robots

Casper Schou, Michael Natapon Hansson, Ole Madsen

Aalborg University, Denmark

This paper presents a configuration framework for assisting shop floor operators in selecting a suitable hardware configuration from commercially available components. The primary focus of this work is the modeling of process, product, and equipment knowledge, and the design of a configurator tool implementing this knowledge. The configurator takes process and product information as input and derives a list of suitable components for the operator to choose from. The approach is verified through a preliminary study indicating the feasibility of the approach.

 
1:50pm - 3:10pmSES 6.2: Digital Product and Process Development
Session Chair: Mika Lohtander
Aula N (first floor) 
 

120. A Cloud-based Kanban Decision Support System for Resource Scheduling & Management

Krishnan Krishnaiyer, F. Frank Chen

The University of Texas at San Antonio, United States of America

For several decades, lean manufacturing methodologies have been used for manufacturing enterprise improvement particularly in operations and supply chain management. As these improvements evolve so does the complexity and the size of data. With the ubiquity of data and the scale of machine automation, abilities for rapid decision making and handling of ever increasing complexity of systems become necessary. The purpose of this research is to demonstrate how a cloud-based Kanban decision support system combined with a robust continuous improvement methodology can help operation managers to make an efficacious decision. Various applications in the literature infer Kanban as a method to control inventory. In this paper, we propose a novel method, Estimated, Actual and Total (EAT) Kanban Decision Support System (DSS) that can be used in any dashboard type monitoring of processes. The paper addresses two research questions: (1) How a robust cloud kanban decision support system will work for a service industry, particularly in resource scheduling and management? (2) Can a proof of concept implementation be scalable across operations management in various sectors? We share successful prototype implementation in Direct Mail Marketing, and Educational Testing product scheduling. The results indicated a dramatic reduction in scheduling time (from 180 minutes to 3 minutes) and the number of tools used (Consolidated 157 spreadsheets into 1 database).


11. Hybrid simulation for complex manufacturing value-chain environments

Cátia Sofia Rodrigues Barbosa1,2, Americo Azevedo1,2

1Inesc Tec, Portugal; 2Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, s/n 4200-465 Porto, Portugal

Simulation is very popular for modelling complex systems. Recent demands from global business optimization, integration of human decision making, and increased complexity of modern systems, push researchers for combining different simulation methods and getting deeper understanding into complex interactions between processes of very different nature, calling for hybrid simulation approaches. These approaches combine at least two of three simulation methods – System Dynamics, Discrete Event Simulation, and Agent Based Simulation.

Even though there is a growing interest in hybrid simulation, many questions remain unsolved, as the lack of a unified use of terms and definitions in the literature, which introduces ambiguity. Literature in hybrid simulation is very sparse, hampering the work of researchers interested in the topic. Many challenges concern authors when using more than one simulation method, as establishing information sharing between the models, converting time units for proper information exchange, the skills required for building the models, among others.

This work aims at providing insight on the use of hybrid simulation in the context of business, supply chains (SCs), manufacturing, and logistics; and the most important advantages and challenges of using hybrid simulation. We try to answer two research questions:

RQ1: How has hybrid simulation been used in business, SCs, manufacturing, and logistics?

RQ2: Which are the challenges and benefits of hybrid simulation compared to standalone simulation?

This paper reviews literature related to hybrid simulation, focusing on different combinations of methods and the advantages and challenges of using hybrid simulations.

For the structured literature review, a set of keywords considering the dispersion of terms in the literature was selected, and three databases (Scopus, Science Direct, and Emerald Insight) were chosen. The papers were filtered based on abstract and full-text reading. Forward and backward search were used for increasing the range of papers analysed. More than 50 papers were fully analysed, across more than 20 years of publications.

Despite all the papers fully analysed targeted hybrid simulations, the modes of operation and relationships established between the models differ. Therefore, it is relevant understanding the different approaches to hybrid simulations. We present a classification scheme for the analysed papers, based on the classification scheme proposed by Swinerd and McNaught (2012), which included interfaced, sequential and integrated classifications, and adding the enrichment taxonomy as in Morgan, Howick and Belton (2016).

Even though hybrid simulation approaches are more frequent, combining two methods is only justified when the developed models are of equal importance to the overall goal of the simulation. Combining models using different methods requires effort and precision to establish information sharing. Common problems which arise include the different time units used in the models. Hybrid models require knowledge about different simulation methods; high skills and flexibility. In spite of the high demands of hybrid simulation, many advantages can be achieved. One of the benefits of hybrid simulation is flexibility. It is possible to simulate different levels of aggregation, avoiding problems of model consistency. Among others, hybridism allows using complementary methods, coupling methods, and exploration of multilateral problems.


90. New Approaches for the Determination of Specific Values for Process Models in Machining Using Artificial Neural Networks

Frank Arnold, Albrecht Hähnel, Andreas Nestler, Alexander Brosius

TU Dresden, Germany

The acceptance of the use of mathematical models for the determination of processforces is directly dependent on the quality of the characteristic values used. Especially in machining, the quality depends on the available information on the entire system machine-tool-material. The permanent development on the system components as well as the use of innovative processing strategies and new methods for processing simulation are drivers of development. An application of powerful mathematical models only makes sense if the specific characteristic values necessary for the process model are present and also up-to-date. In order to ensure this up-to-date, considerable effort is required to determine these variables. This time and cost implementation makes the application of process models unattractive in industrial applications. For the determination of the specific cutting forces of the cutting force model according to Kienzle, machining tests have to be prepared, carried out and evaluated. This requires the knowledge of an expert as well as the use of additional measuring technology. As a rule, these expenditures are not operated, which means that the available potentials in the overall system machine-tool-material are not used extensively. The approach of automated data acquisition without the need for additional measuring technology in the cutting machine is one possibility of a broader application. Modern CNC offer extensive information and communication functions. A concept for the detection of selected dynamic process data is developed and implemented using the example of the determination of specific cutting forces for the cutting force model according to Kienzle on the application of 2.5D milling. The processing of the discrete process data, which is recorded directly at the CNC, with different mathematical approaches is investigated and evaluated. Special attention is given to a separation of the signals into the components from the basic behavior of the machine and the fractions from the machining process itself as well as a clear detection for an automated evaluation. The following illustration of the recorded process data on the physical variables allows the determination of the specific cutting forces. This process can be carried out concurrently and is not a significant additional effort. Using the machine learning with artificial neural networks using the ability to generalize, specific characteristic values are determined on the basis of process data. This allows mathematical models to be supplied with current characteristic values over a wide range of applications. A major application is seen in the improved design of machining processes.


229. The Evaluation of Resonance Frequency for Piezoelectric Transducers by Machine Learning Methods

Fengming Chang

National Taitung Jr College, Taiwan

A piezoelectric transducer is a component employed in the applications of transmitting and receiving of sound wave. The distance of the sound wave could send is determined by the transducer frequency. Therefore, to measure the frequency becomes an important issue. However, it needs a lot of experiments to simulate and measure the transducer’s resonance frequency in the laboratory. To solve this problem, this research estimate a transducer’s frequency by machine learning methods instead of a laboratory experiment. The proposed method are compared with other methods, such as artificial neural network, support vector machine, C4.5, neuro-fuzzy, and mega-fuzzification. The results show that machine learning methods are efficiency ways to assess the resonance frequency of a piezoelectric transducer. Besides, mega-fuzzification method has the best accuracy among the comparative methods in this case.

 
1:50pm - 3:10pmSES 6.3: Manufacturing Process and Technology
Session Chair: Francisco J. G. Silva
Aula O (first floor) 
 

76. On the feasibility of determining the Heat Transfer Coefficient in casting simulations by Genetic Algorithms

Anastasia Vasileiou1, George-Christopher Vosniakos2, Dimitrios Pantelis3

1The University of Manchester, Sackville street, Manchester M13 9PL, UK; 2National Technical Univerity of Athens, School of Mechanical Engineering, Heroon Polytehneiou 9, 15780 Athens, Greece.; 3National Technical Univerity of Athens, School of Naval Architecture and Marine Engineering, Heroon Polytehneiou 9, 15780 Athens, Greece.

In studying metal casting using simulation with commercially available software, the Heat Transfer Coefficient (HTC) between the casting and the mould surrounding it is not known, yet it is required and its influence on the accuracy and credibility of results is crucial. Temperature distribution, phase changes and mechanical properties as well as defects may appear significantly different to reality depending on the HTC employed in the simulation. Thus, typical HTC values are adopted, as commonly suggested by the software’s developpers. Furthermore, the HTC may differ from region to region, mainly due to the local casting modulus, i.e. the ratio of volume to surface of the different bodies that may comprise the casting. As a solution, it is suggested to use an intelligent search methodology based on a genetic algorithm (GA) that can presumably determine the correct value of HTC or indeed the different HTCs. The GA in essence tries different HTC values on the simulation program stochastically, until a stopping criterion is reached. The latter consists of an acceptably low difference between the real and simulation curves of temperature versus time at one or more points of the casting. In order to test this methodology, numerical casting experiments were conducted using a simple as well as a more complex casting geometry. The numerical casting experiments were conducted on ProcastTM assuming specific HTC values and, as a result, the temperature versus time curve for particular points of the casting were obtained. Then, the GA was setup and the HTC search methodology described above was implemented. In both casting cases, the GA succeeded in finding the HTC values originally employed. Furthermore, the influence of the most important GA parameters on the accuracy and speed of reaching the desired HTC values was explored.


98. Optimization of high pressure die casting process regarding small parts in zamak alloys

Helder Alexandre Pinto, Francisco J. G. Silva

Instituto Superior de Engenharia do Porto, Portugal

The casting industry is one of the major industries in the world with a great impact in everybody`s life. Casted products can be found all over around, since the most tiny part like a bottom to the biggest naval ship motor parts and carcasses, all made by casting processes. The demand for a high quantity of products in order to respond to a higher demanding market, turn on the need to develop this casting process, creating a new branch in this industry, the die casting.

Die casting is a process where a permanent mould is used, and melted metal is injected by pressure, allowing smaller cycles and continuum parts production.

Die casting can be carried out in various ways, depending on the need of the project, depending on the need to have parts presenting finished bright and polished look if we are working in the decoration area, or in other hand we may need solid and resistant parts, if these ones are to be implemented in functional demanding works. The results will only depend on the parameters used in the process and on the molds design. The functional parts are far the most demanding in the parameters requirements, being need to have additional attention to avoid defects in the final product like porosities, segregations, cold joint, inclusions and incomplete fill that can occur due to temperature, pressure, retained gases, unappropriated cycle time or other points that might interfere with the casting.

This study is focused in die casting applied to automobile industry where many casted parts are used in their components. Car doors are no exception; therefore, zamak casted parts are used in command cables as cable cuts and working as functional parts. Is then necessary to have a very precise control over the entire casting process, so these parts can be obtained with less defects.

The study is then based on three different samples that are already in production, by analyzing their status as casted and identifying their defects by using magnifier views and x-ray exams. A second phase is then initiated with the help of finite elements software (FEM) dedicated to casting processes; here the main goal is to establish all the parameters to be improved, as well as the mould design in a way to obtain the finest parts as possible by the elimination of the defects that where obtained by the previous way.

The premises according to NADCA standards were established, so that all the existing and future parts could be created with excellent quality, as required by automobile industry.


115. Analytical cost estimation model in High Pressure Die Casting

Claudio Favi1, Michele Germani2, Marco Mandolini2

1Università degli Studi di Parma, Italy; 2Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via brecce bianche 12, 60131, Ancona, Italy

The present paper aims at the definition of an analytical model for the cost estimation of the High Pressure Die Casting (HPDC) process, which is based on two main pillars: (i) knowledge collection and (ii) cost estimation rules. The novelty of this approach is link between the analytical model (equations) and the geometrical features of the product under development. The relationship between geometrical features and cost items gives an accurate result in terms of cost breakdown and it can be used by product designer as a powerful tool for the application of Design-to-Cost rules in HPDC sector


171. Hot forging operations of brass chips for material reclamation after machining operations

Jakob Johansson, Lisa Ivarsson, Jan-Eric Ståhl, Volodymyr Bushlya, Fredrik Schultheiss

Lund University, Sweden

Metal cutting chips are a by-product of all machining operations. When manufacturing components by machining, it is not unusual that a majority of the workpiece material is converted to chips. The chips from the cutting process needs to be disposed of in some way; the most common practice in industry is to send the chips back to the material supplier for recycling.

In this paper a method of recycling chips derived from the brass alloy CW614N by use of hot forging operations is presented. The general idea for the developed method is to find a relatively simple procedure that is possible to implement for recycling of materials in-house at small and medium sized enterprises, SMEs. By applying hot forging methods on pre-compacted cutting chips, it may well be possible to successfully forge blanks for subsequent machining having the same, or nearly the same, mechanical properties and application as a blank forged from raw material.

The results presented in this paper show the result from initial experiments for evaluating if the envisioned process is possible to implement, and which process parameters to evaluate to enhance future development of the method.

Experiments have been made regarding density of forged blanks, machining and function tests as well as Energy Dispersive X-ray, EDX, analysis on the chemical composition.

Density measurements show that the hot forged blanks all have close to the same density when compared with the raw-material.

A standardized function test used in industry for the machined components was performed on blanks machined to a finished product. The function test shows an acceptance rate of 62.5 percent for parts forged with chips derived from brass alloy CW614N.

Alloys containing zinc can be difficult to sinter due to the propensity for dezincification and therefore EDX-analyses of the chemical composition was made. When heating the material to forging temperature, there is a risk of changing the materials chemical composition compared to the raw material. The EDX-analyses show no difference in chemical composition between the raw material and the hot forged blanks. EDX line scan analyses show difusion bonding between some chips, forming a uniform material without significant changes in chemical composition. A few chip boundaries exist in the microstructure but the fact that some difusion bonding between chips has occurred shows that the tested method has a possibility to be implemented in the industry in the future after further development.

Thus, the current research show that partial difusion bonding between the chips has occurred and created a homogenous microstructure indicating a future potential for the envisioned process. This is further aided by the notion that heating and forging processes do not appear to affect the chemical composition of the material. However, additional research is needed before industrial implementation even though the evaluated method shows promising results.

 
1:50pm - 3:10pmSES 6.4: Engineering Collaboration for Smart Manufacturing
Session Chair: Roberto Raffaeli
Aula P (first floor) 
 

121. High frequency and radicality of product innovation and high flexibility and agility of system of manufacturing: Towards the Smart Factories

Martins Oliveira

Federal Fluminense University, Brazil

This research aims to verify the correlation between the high frequency and high radicality in product innovation and high flexibility and high agility in manufacturing process in smart factories. Furthermore, this research examines how the high flexibility and high agility affect the Companies performance (results). A conceptual framework is drawn up based on the literature and confirmed with specialists. The model was tested on 15 manufacturing plants in innovative Companies (Apple, BMW, General Electric, IBM, Novartis, Philips, Samsung, Siemens, Tesla Motors, and Toyota, others) in Asia, Europe and United States. The research involved the intervention of experts, selected according to their technical-scientific criteria (production managers, product innovation managers, R&D managers, others). The data were extracted by means of a matrix of judgement in which experts made their judgments about the variables investigated (a Survey). To reduce subjectivity in the results achieved the following methods are used complementarily and in combination: multicriteria analysis, multivariate analysis, and neurofuzzy technology. In fact, production issues are rapidly emerging as one of the most important topics in strategic manufacturing decisions. In this sense, the innovation may represent a strategic tool, increasing the institutional capacity of smart companies in their assignments of formulation, evaluation and execution of such projects of products innovations. Furthermore, the integrated use of agility and flexibility manufacturing practices promotes manufacturing competitive strength. This study intends to fill an existing gap in literature between the high radicality product innovation and high agility and flexibility towards the smart factories. Companies that pursue smart manufacturing agility and flexibility should develop innovation capabilities to obtain an improvement on results performance. The high radicality in products innovations is positively associated with new product performance. The study offers clear guidance to management on ways of stimulating the flexibility and agility in radical innovation context of smart manufacturing.


291. The application of reference ontologies for semantic interoperability in an integrated product development process in smart factories

Anderson Luis Szejka, Osiris Canciglieri Junior

Pontifical Catholic University of Parana, Brazil

The modern manufacturing industry has been challenged to be highly flexible in bringing to the market new products, using extensive integration between customers, companies, and suppliers. The concept of Smart Factories requires efficient and effective information sharing between different phases of Product Development Process since multiple stakeholders are involved within and across the enterprise boundaries. Efficient and effective information sharing demands formal information structures in order to make sure the semantic interoperability across different phases of Product Development when multiple domains are involved in the process. The premise of the research is that the ontology provides the reference for determining the semantic interoperability across heterogeneous domains. In this context, this research presents an application of reference ontologies to support semantic interoperability during the Product Development Process in Smart Factories. The concepts inherent to the product development process are formalized in core reference ontologies that represent in an elementary way the information data structure. The core ontologies are specialized according the specific product data in order to support product design and manufacturing. A case study in thin wall plastic injected product is performed to evaluate the approach potential to aid the information sharing in the integrated product development process in Smart Factories. As a result, the potential benefits and limitations of the ontology-driven interoperability were discussed, contributing to the semantic interoperability field and improving the development of modern manufacturing industry.


360. Design and Analysis of Tungsten Carbide Sludge Removal Machine for Maintenance Department in Cutting Tool Manufacturer

Syahmi Shahar, Noor Azlina Mohd Salleh

Universiti Teknologi MARA Malaysia, Malaysia

In Cutting Tool Industries, the grinding process for producing cutting tools creates carbide sludge which is a combination of carbide waste from the product material and coolant from the grinding machine. Since carbide sludge will be filtered in the filter machine, a monthly maintenance is necessary for the filter machine which include transferring accumulated carbide sludge into the waste barrel. The current process of removing carbide sludge from the filter machine required 2 to 3 person and takes a considerate amount of time. The process also require several types of equipment such as jack and forklift which require skilled workers to operate. This research aim to develop a carbide sludge remover machine that fits perfectly into ABC Cutting Tool Industries production line. Methodology used for this research is by following Deming Cycle Approach (PDCA), observation, conceptual generation through PUGH method and design software (CATIA). The benefit of this research is a design and analysis of carbide sludge remover machine that could reduce the number of workers required for the waste removal process. It also simplifies the operation of removing carbide sludge from the filter machine. This research may contribute to the cost reduction for the carbide sludge removal process overtime and also improve the safety of the operator. Besides that, a fully automated Carbide Sludge Remover can also be the next part of this research as well as the intelligent carbide sludge indicator sensor that linked with the operation of the company.


353. A Novel Concept Of Production And Assembly Processes Integration

Bruno Miguel Moreira, Ronny Miguel Gouveia, Francisco Silva, Raul Campilho

ISEP – School of Engineering, Polytechnic of Porto – Department of Mechanical Engineering, Portugal

Due to cost pressure, shortened development cycles, as well as increasing variety and technical product complexity, companies face more complex parallel development processes. Automating a manual process can greatly increase the productivity of a

manufacturing facility. It can reduce overall system life cycle costs, reduce machine start-up time, and improve product quality and consistency. This work intends to show the real advantages of processes’ integration in opposition to a diversity of interdependent automated processes, in terms of work preparation (setups), materials flow and maintainability. A case study is presented, illustrating how the system can be designed, establishing a novel concept of fully-automated equipment integrated production and assembly systems.

 
1:50pm - 3:10pmSES 6.5: Smart Factories and Industrial IoT
Session Chair: Luca Pazzi
Aula Q (first floor) 
 

75. An embedded database technology perspective in cyber-physical production systems

Andrea Bonci, Massimiliano Pirani, Sauro Longhi

Università Politecnica delle Marche, Italy

The goal of the paper is the proposition of an enabling technology for the control and optimization of cyber-physical production systems, oriented to the lightweight implementation of performance metrics methodology in a network of distributed devices. The database-centric perspective, applied to distributed devices, supports the adoption of well-known key performance metrics for viable lightweight control policies and optimization of complex scenarios in the factory of the future. An experiment of the technique on a real case data set is presented and analyzed.


1. Context related information provision in Industry 4.0 environments

Hendrik Unger, Frank Börner, Egon Müller

Technische Universität Chemnitz, Germany

In Industry 4.0 there are several fields of work. Next to Social Machines, Virtual Production, Smart Products and Global Facilities a main field is Augmented Operators. To be able to assist people in their work, it is necessary to reduce the amount of data that is needed to be perceived in any given moment. In current systems more and more data is generated from day to day and has to be evaluated to be helpful. For many tasks only a certain part of the general information flow is relevant. An information demand analysis can help reducing big data to smart data and identifying possible context key factors. Using such factors information can be categorized and provided when the context is right. This article shows the interpretation of several information demand analysis as well as the development of a demonstrator application for context related information provision based on the findings.

© 2017 The Authors. Published by Elsevier B.V.

Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing.


355. From the Internet of Things to Cyber-Physical Systems: the Holonic Perspective

Luca Pazzi, Marcello Pellicciari

Unimore, Italy

The paper presents a distributed model for implementing Cyber-Physical Systems aimed at controlling physical entities through the Internet of Things. The model tames the inherent complexity of the task by a recursive notion of modularity which makes each module both a controller and a controlled entity. Each module hosts a state-based behaviour which is able to play alone both roles seamlessly and simultaneously. The controller part is implemented within the module through specific constructs, which are not visible when the module acts as a controlled entity. Vice versa, other constructs of the behaviour, which constitute its interface, allow to act upon it when the module plays the role of controlled entity. Controlled and controller modules communicate through events, grouped in different typologies according to the role they are called to implement. Through such events, modules receive commands and give feedback when controlled; vice versa when acting as controllers, they send commands and receive feedbacks to which react. The model thus allows to decomposes feedback loops by the modular structure. Modules are arranged along part-whole tree-like hierarchies which collectively constitute the system. Nodes which interact directly with the physical world are the leaves of such trees. Root and leaf nodes can be added in order to extend the system. The behaviour of each module is strictly local since it has visibility only on its controlled modules, but not on the module which controls it. Such locality and limited visibility increases the reusability and reduces the complexity of the module. Each behaviour can be directly checked at design time against temporal logic formulas related to the joint behaviour of its controlled entities. Once checked, the holon to which it belongs it can be composed into more complex holons preserving the validity of the formulas, thus encapsulating safety and liveness properties.

 
1:50pm - 3:10pmSES 6.6: Product and Process Design
Session Chair: Serena Graziosi
Aula R (first floor) 
 

380. Influence of manufacturing constraints on the topology optimization of a high performance automotive dashboard.

Sara Mantovani1, Ignazio Lo Presti1, Luca Cavazzoni1, Andrea Baldini2

1University of Modena e Reggio Emilia, Italy; 2Ferrari S.p.A, Via Abetone Inferiore 4, 41053 Modena, Italy

Topology Optimization (TO) methods optimize material layout to design light-weight and high-performance products. However, TO methods, applied for components or assembly with high complexity shape or for structures with copious number of parts respectively, do not usually take into account the manufacturability of the optimized geometries, then a heavy further work is required to engineer the product, risking to compromise the mass reduction achieved. Within an Industry 4.0 approach, we propose to evaluate manufacturing constraints since early stages of the conceptual design to perform a TO coherent with the manufacturing technology chosen. Several approaches of TO with different manufacturing constraints are proposed and each solution is compared. The optimum conceptual design is determined in order to minimize the component weight while satisfying both the structural targets and the manufacturing constraints; a case study on a high-performance sport car dashboard is finally presented.


381. A Practical Method for Determining the Pseudo-Rigid-Body Parameters of Spatial Compliant Mechanisms via CAE Tools

Pietro Bilancia, Giovanni Berselli, Luca Bruzzone, Pietro Fanghella

Univeristy of Genoa, Italy

Compliant Mechanisms (CMs) are currently employed in several engineering applications requiring high precision and reduced number of parts. For a given mechanism topology, CM analysis and synthesis may be developed resorting to the well-known Pseudo-Rigid Body (PRB) approximation, where flexible members undergoing large deformations are modelled via a series of spring-loaded revolute joints. The PRB approach is not only intended as a design tool for the first attempt sizing of the mechanism, but it is also useful for reducing computational costs during simulation and control of engineering systems containing compliant members. Owing to these considerations, this paper reports about a practical method to determine accurate PRB model of CM comprising out-of-plane displacements and distributed compliance. The method leverages on the optimization capabilities of modern CAE tools (i.e. Recurdyn Software), which provides built-in functions for modelling flexible members during their motions. Simulations are initially performed on an elementary case study, concerning a fixed-guided beam-like flexure, whose aim is to validate the method by comparing analytical and numerical results. Then, an industrial case study, which consists of a crank mechanism connected to a fully-compliant four bar linkage is discussed. The resulting PRB, which comprises four spherical joints with generalized springs mounted in parallel, shows performance comparable with the deformable system.


93. Self-aware Smart Products: Systematic Literature Review, Conceptual Design and Prototype Implementation

Marcelo Feliciano Filho, Yongxin Liao, Eduardo Rocha Loures, Osiris Canciglieri Junior

Pontifical Catholic University of Paraná - PUCPR, Brazil

Nowadays, during the manufacturing processes, lots of data are generated by various information systems along production lines. However, most of them are mainly used as a statistic for supporting the manual, semi-automatic or automatic decision makings. The fourth industrial revolution is the key to make more effective use of those data and to create a more interconnected smart manufacturing industries all around world. In which, machines can communicate not only with one other (Machine to Machine), but also, more directly, with products themselves, through the application of IoT (Internet of Things). This trend demands a product to know itself, namely self-awareness smart product. The data that stored inside a product throughout its life cycle is created, updated and protected in real time. It is currently becoming a reality to speed up the transformation from the traditional mass-production to the modern mass-customization. Producers and customers of a smart product can both benefit from what this new industrial revolution wave provides. The main objective of this paper is firstly to scientifically explore the state of art about the smart product in Industry 4.0 through a Systematic Literature Review (SLR). Second, to design a smart factory production environment based on the SLR findings (e.g. the most recognized software, hardware, and standards). Finally, to implement a self-awareness smart product prototype in this scenario by integrating the Near Field Communication technologies (such as RFID), internet accessible equipment (such as industrial robotic arm, programmable logic controller, Raspberry Pi, and Lego™ Mindstorm), and Cloud services (such as IBM Bluemix).


176. Designing for Metal Additive Manufacturing: a case study in the professional sports equipment field

Serena Graziosi1, Francesco Rosa1, Riccardo Casati1, Pietro Solarino2, Maurizio Vedani1, Monica Bordegoni1

1Politecnico di Milano, Italy; 2Fonderia Maspero s.r.l., Via Ercolano 2, Monza, 20900, Italy

In this paper, we discuss the possibilities available as well as the challenge to be faced when designing for metal additive manufacturing through the description of an application of the Selective Laser Melting technology within the professional sports equipment field. We describe the redesign activity performed on the cam system of a compound bow, starting from the analysis of the functional, manufacturing and assembly constraints till the strategies applied to guarantee the printability of the object. This activity has thus provided the opportunity to analyse the difficulties currently encountered by practitioners when designing for additive manufacturing due to the lack of integrated design approaches and the high number of aspects that need to be simultaneously taken into account when performing design choices.

 
3:10pm - 4:05pmKEY 4: Keynote Speech 4 (Aydin NASSEHI)
Proactive decision making in future production enterprises: the role of big data, internet of things and cyberphysical systems
Aula Convegni (first floor) 
4:05pm - 4:30pmCoffee break
Gallery at first floor 
4:30pm - 5:50pmSES 7.1: Robots in AVM
Session Chair: Georgios Michalos
Aula Convegni (first floor) 
 

255. Cognitive Robot Referencing System for High Accuracy Manufacturing Task

Cristina Cristalli, Luca Lattanzi, Daniele Massa, Giacomo Angione

AEA s.r.l. - Loccioni, Italy

Industrial robots can be considered very repeatable machines, but they usually lack of absolute accuracy. However, high accuracy during the execution of the task is becoming a more and more critical factor in industrial manufacturing domains. For that reason, in order to fully automatize manufacturing processes, high-precision tasks usually need the integration of additional sensors to improve robot accuracy. This paper proposes an embedded, cognitive and self-learning stereo-vision system that can be used to reference the robot position with respect to the work-piece, increasing robot accuracy locally. An industrial use-case is also proposed and experimental results are presented.


284. A machine learning approach for visual recognition of complex parts in robotic manipulation

Panagiotis Aivaliotis, Anastasios Zampetis, Georgios Michalos, Sotiris Makris

Laboratory for Manufacturing Systems and Automation (LMS), Greece

The research presents a method for visual recognition using machine learning services for complex part manipulation. The robotic manipulation of complex parts is an application with high uncertainty caused by the instability of gripper’s grasping. The accurate estimation of part’s position and orientation after grasping it is needed in order to execute successfully a manipulation task. A visual recognition approach using classifiers is implemented for the accurate estimation of part’s position and orientation. Finally, a case study of the robotic manipulation of complex parts using the machine learning services for visual recognition is demonstrated and evaluated.


286. Flexible programming tool enabling synergy between human and robot

Stereos Alexandros Matthaiakis1, Konstantinos Dimoulas1, Athanasios Athanasatos1, Konstantinos Mparis1, George Dimitrakopoulos1, Christos Gkournelos1, Apostolis Papavasileiou1, Nikos Fousekis1, Stergios Papanastastiou1, Georgios Michalos1, Giacomo Angione2, Sotiris Makris1

1Laboratory for Manufacturing Systems and Automation (LMS), Greece; 2AEA s.r.l , Loccioni Group, Via Fiume 16, 60030, Angeli di Rosora (AN), Italy

This paper discusses a method for flexible robot programming and execution control, enabling human-robot collaborative tasks. This method considers data that are initially generated through an offline programming tool and are corrected online considering feedback from force and vision sensors. A number of tasks is dynamically assigned to both human and robot resources. The user tests the programming result through an external control system. The initially assigned tasks can be online re-assigned. The method has been implemented on the top of ROS as an android application and has been applied in automotive and aeronautics industries for screwing and inserting operations.


28. Reinforcement Learning for Manipulators Without Direct Obstacle Perception in Physically Constrained Environments

Marie Ossenkopf1, Philipp Ennen2, Rene Vossen2, Sabina Jeschke2

1Universität Kassel, Germany; 2Institute of Information Management in Mechanical Engineering, RWTH Aachen University, Dennewartstr. 25, 52068 Aachen, Germany

Adapting a robotic assembly system to a new task requires manual setup. This represents a major bottleneck for the automated production of small batch sizes. One approach to reduce manual ramp-up time is to make the manufacturing system self-learning [Baroglio et al. 1996, Ennen et al. 2016].

Serial manipulators in industrial use for assembly or pick&place tasks yield high physical danger for themselves and their environment. The physical danger emerges from potential collisions of the robot with obstacles in the environment. Without knowledge or sensing of the obstacles it is not possible to avoid a collision in the first place. The robot is also endangered by movements that try to exceed its mechanical constraints with respect to maximum joint angles, maximum velocity and maximum acceleration. This becomes critical in the free exploration phase of a learning process. Learning algorithms for use on industrial serial manipulators therefore need to be adapted to meet this problem.

We present two enhancements of the Relative Entropy Policy Search (REPS) algorithm [Peters 2010] that enable a robot to: (1) detect collisions during the learning process, (2) react to these collisions, (3) learn from these collisions and (4) avoid to plan movements outside the maximum joint angles. The enhancements utilize Dynamic Movement Primitives (DMPs) as policy representation. DMPs are an established policy representation for serial manipulators [Schaal et al. 2005, Ijspeert et al. 2002, Deisenroth et al. 2013]. They map an acceleration onto a position and a velocity in state space by modeling every dimension as a spring-damper-system. To be independent of the kinematic model, we use the dimensions of the robot’s joint angle space instead of world coordinates.

In particular, the two enhancements are: (1) We integrate potential fields into the DMPs to lower the possibility of exceeding the maximum joint angles. (2) We monitor the deviation between the planned trajectory and the current position to detect collisions and the exceedance of mechanical constraints. This enables us to interrupt a colliding movement. The deviation is also used as an evaluation of the policy.

The new features work on any serial robot with an angular encoder. There is no need of additional sensors, an elaborated vision or modeling of the environment. The approach is independent of the knowledge of the kinematic and dynamic model of the robot, so no exact model has to be determined and the algorithm stays unaffected by model errors. The obstacle avoidance can be learned without knowledge of the obstacles. Hence, these additional properties reduce the requirements imposed on the assembly system and the ramp-up time.

We tested the algorithm in a simulation of the ABB IRB120 robot. As evaluation task we used a simple reaching task with obstacles. We show that the exceedance of maximum joint angles can be significantly reduced, that collisions can be detected instantaneously, and that the algorithm learns to avoid experienced collisions.

 
4:30pm - 5:50pmSES 7.2: Production Planning and Scheduling
Session Chair: Esther Álvarez de los Mozos
Aula N (first floor) 
 

118. Considering the Effects of Pre-Set Service Level and Actual Service Level in a Safety-Stock Based SPIRP

Ehsan Yadollahi1,2, El-Houssaine Aghezzaf2, Joris Walraevens1, Birger Raa2

1Gent University, Belgium; 2Department of Industrial Systems Engineering and Product Design, and Flanders Make,

To deal with uncertain demand rates in stochastic periodic inventory routing problem (SPIRP), supply chain planners foresee an extra stock amount, known as “safety stock” at the retailers. This safety stock prevents stock-out and gives the supply chain planner the possibility to offer a level of service assurance to serve the retailers. The pre-set service level for the retailers guarantees the reliability of having the demand rates satisfied at a certain rate during the planning horizon. To prove the guaranteed service level at the retailers, the actual service level is measured in a simulation experiment with multiple scenarios. The problem is that the difference between the actual and pre-set service level does not behave linearly for the different scenarios. In addition, this non-linearity changes with the length of the planning horizon. In this paper, we evaluate the behavior of the actual service level compared to the pre-set service level. Also the effects on short/long term planning horizon is measured and analyzed. A case study of a distribution center is considered to show how to optimize the inventory level and routing system with different planning horizon and pre-set service level. We simulate the optimized solutions to evaluate the service level behavior.


41. Evaluation of the effect of product demand uncertainty on manufacturing system selection

Ana Vafadarshamasbi, Majid Tolouei-Rad, Kevin Hayward

ECU Westeran Australia University, Australia

Market competition is leading manufacturers to utilise advanced manufacturing systems. This paper focuses on a relatively new manufacturing system which provides a flexible and modular platform for drilling-related operations within automotive component industries. The use of these systems which include modular machine tools is widespread; however, manufacturers wishing to choose this technology, frequently face selecting the most appropriate and productive manufacturing system versus different available alternatives. Besides, due to the fact that today manufacturers face uncertainty of product demand, this process becomes more difficult as a lot of factors are influenced by demand variation simultaneously. Accordingly, a reliable decision should be made before making an investment on the production method. The aim of this research is analysing the sensitivity of demand uncertainty on the economic performance of modular drilling machine tool versus other alternatives and is evaluating the uncertainty’s impacts on the decision making process. To do so, a model is suggested which helps in machine tool evaluation for producing a given part to select the most productive machine tool. In this model, the demand is assumed to be independent and uncertain. Accordingly, the parameters which are influenced by demand are identified and the contribution of demand uncertainty in these parameters are investigated. Three automotive parts of varying complexity are used to examine the proposed approach and the results are discussed. The results show that considering demand uncertainty in the manufacturing system selection problem provides critical information and leads users to make logical and reliable decisions.


345. Efficient machine layout design method with a fuzzy set theory within a bay in a TFT-LCD plant

Teng-Sheng Su, Ming-Hon Hwang

Chaoyang University of Technology, Taiwan

Building a thin-film transistor liquid-crystal display (TFT-LCD) plant is a huge investment, as a result TFT-LCD designers have been looking to a good layout design to increase their production efficiency. A multiple-zone in-line stocker is the plant’s intra-bay automated material handling system (AMHS). Due to the unique multiple-zone characteristic, the machine layout in a TFT-LCD bay is different from that in a semiconductor bay. The machine layout design within a TFT-LCD bay is required to solve not only the machine grouping problem, but also the zone formation problem. Furthermore, except for precisely quantitative criteria, vague information provided by the human natural language is a part of inputs to the machine layout design. A method capable of taking designers’ linguistic variables, like low, medium, and high, into consideration in producing a machine layout of a TFT-LCD bay is becoming more important. In this paper, we propose an efficient machine layout design method with a fuzzy set theory within a bay in a TFT-LCD plant. An intelligent hybrid heuristic algorithm with a mixed integer linear programming (MILP) model is developed. The objective aimed to achieve is to maximize in-sequence movements and minimize backtracking movements, the total flow distance, and the total backtracking flow distance. An example is given to illustrate the proposed layout procedure. It is our hope that the proposed approaches from this study benefits TFT-LCD designers to deal with both quantitative and linguistic variables for their machine layout problems.


314. Evaluation of interoperability between automation systems using multi-criteria methods

Maicon Saturno1,2, Luiz Felipe Pierin Ramos1, Fabricio Polato1, Fernando Deschamps1,3, Eduardo de Freitas Rocha Loures1,4

1Pontifical Catholic University of Parana (PUCPR), Brazil; 2Dominus – Automação, Sistemas e Acionamentos, Avenida Manoel Ribas, 8.120 Curitiba, Paraná, Brazil; 3Department of Mechanical Engineering (DEMEC), Federal University of Paraná (UFPR), Rua Coronel Francisco Heráclito dos Santos, 230 Curitiba, Paraná, Brazil; 4Department of Electro-tecnology (DAEL), Federal University of Technology – Paraná (UTFPR), Avenida Sete de Setembro, 3033 Curitiba, Paraná, Brazil

The business model of many companies is based on the customization of the products in the portfolio. The request for proposal and quotation moves from the product technical requirements and starts a negotiation phase ending with the offer generation. Usually, a simplified but complete design process is needed involving time-consuming activities and technical expertise. It has been observed that many companies just base the process on poor empirical models working by analogy on the basis of the expertise of senior designers and searching for similar past solutions. Then, product BOM is adapted and costs are updated accordingly.

In addition, design considerations and choices should not be limited to manufacturing cost evaluations. Environmental concerns pushes toward the early analysis of the lifecycle cost of a product, including the use and end-of-life phase. Indeed, the investment costs for tooling, accessory plants, and assets in general, needs to be included in the analysis as well as the technological background of the producer and the available IT infrastructure.

On the basis of such considerations, a research program has been started aiming at conceiving a tool to support stakeholders in the process of the early estimation in the view of the entire life-cycle of the new product. The paper investigates the requirements of such a tool on the basis of the literature background and the industrial needs. A structure of the system is depicted along with the main functionalities that should be provided.

One of the main issue regards the data exchange between the tool and other company software (e.g. CAD, ERP, PLM, KBE). Integration is needed in order to avoid information redundancy, while functionalities overlap between different systems is to be avoided. On the contrary, original functionalities are highlighted.

The framework has been proposed to a panel of partner companies that have shown interest for the system. Functionalities and benefits of the tool have been analyzed toward each company context.

The paper reports the output of the interviews with the stakeholders. The expectations of the companies have been analyzed and synthetized in a list of requirements which have been sorted and prioritized. Directions for the design and implementation of the system are finally proposed at the end of the paper.

 
4:30pm - 5:50pmSES 7.3: Robotics and Computer Integrated Manufacturing
Session Chair: Michele Gadaleta
Aula O (first floor) 
 

375. PRM Based Motion Planning for Sequencing of Remote Laser Processing Tasks

Sigurd Lazic VIllumsen, Morten Kristiansen

Aalborg Universitet, Denmark

The mechanical system used for remote laser processing can contain as much as 9 degrees of freedom (DOF). In this paper, a sample based motion planning algorithm for such remote laser processing equipment is presented. By construction robot configurations through a sampling strategy redundancy is inherently taken into account and the path is ensured to comply with laser processing constraints. A test showed that the algorithm was capable of finding 1277/1280 possible paths in 2000 iterations for a 9 DOF mechanical system. These 1277 paths were represented in matrix form which can be used for sequencing of laser processing tasks.


220. Automatic Path Planning of Industrial Robots Comparing Sampling-Based and Computational Intelligence Methods

Lars Larsen1, Jonghwa Kim2, Michael Kupke1, Alfons Schuster1

1German Aerospace Center, Germany; 2University of Science & Technology (UST),217 Gajeong-ro, 34113 Daejon, Korea

In times of industry 4.0 a production facility should be “smart”. One result of that property could be that it is easier to reconfigure plants for different products which is, in times of a high rate of variant diversity, a very important point. Nowadays in typical robot based plants, a huge part of time from the commissioning process is needed for the programming of collision free paths. This mainly includes the teach-in or offline programming (OLP) and the optimization of the paths. To speed up this process significantly, an automatic and intelligent planning system is necessary. In this work we present a system which can plan paths industrial robots. We compare widely used sampling-based methods like PRM or RRT with Computational Intelligence (CI) based methods like genetic algorithms.


260. Theoretical and Kinematic Solution of High Reconfigurable Grasping for Industrial Manufacturing

Carlo Canali, Nahian Rahman, Fei Chen, Mariapaola D’imperio, Darwin Caldwell, Ferdinando Cannella

Istituto Italiano di Tecnologia, Italy

High flexibility and high speed is the goal for industrial manufacturing. However, it is difficult to put them together due to the reason that they are contradicting with each other. The authors face this production process problem and presented a new high reconfigurable gripper. It has two degrees of freedom per finger and can support enough payload for manufacturing applications. At same time the simple kinematics permits to be fast. Moreover, not only it is able to handle different workpiece, but the same design concept, can be applied to different scenario. In this paper the authors motivate and detail all the principals and the concepts used for define and design this gripper. The physical models are shown as proof of this successful project.


386. A Simulation Tool for Computing Energy Optimal Motion Parameters of Industrial Robots

Michele Gadaleta2, Giovanni Berselli1, Marcello Pellicciari2, Mario Sposato2

1University of Genova, Italy; 2Enzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, Via P. Vivarelli, 10, 41125 Modena, Italy

This paper presents a novel robot simulation tool, fully interfaced with a common Robot Offline Programming software (i.e. Delmia Robotics), which allows to automatically compute energy-optimal motion parameters, for a given end-effector path, by tuning the joint speed/acceleration during point-to-point motions whenever allowed by the manufacturing constraints. The main advantage of this method, as compared to other optimization routines that are not conceived for a seamless integration with commercial industrial manipulators, is that the computed parameters are the same required by the robot controls, so that the results can generate ready-to-use energy-optimal robot code.

 
4:30pm - 5:50pmSES 7.4: Data Analytics in Manufacturing and Services
Session Chair: Mika Lohtander
Aula P (first floor) 
 

86. Advanced use of data as an enabler for adaptive production control using mathematical optimization – an application of Industry 4.0 principles

Johan Vallhagen1,2, Torgny Almgren1,2, Karin Thörnblad1

1GKN Aerospace Engine Systems, Sweden; 2Chalmers University of Technology, 412 96 Gothenburg SWEDEN

For a long time, it has been a well known fact that variation leads to production inefficiency. The reduction of variations has therefore been one of the starting points for successful production control strategies such as Lean and variants of the Toyota Production System. Some businesses do not, however, lend itself easily to this type of standards and logic. An example is the production of jet engine components and aircraft components that often are produced in functional workshops. For different reasons, dedicated product flows are difficult to motivate and results in solutions where a large mix of low volume products have to share a limited amount of resources. This may create complex flows where the planning and control conditions are subjected to constant change.

This type of production logic therefore demands a more adaptive production control to reach high efficiency, something that previously has been hard to achieve due to the lack of the required data and computational methods. The use of modern industrial IT solutions enables real time access to large amounts of data, which creates new possibilities when these data are combined with modern data management and recent findings in optimization methodology.

GKN already uses advanced optimization algorithms to schedule individual production cells, for example in a heat treatment facility which is a shared resource for many products. The results in implemented shop areas have shown considerably improved throughput and shorter lead times. The experiences, so far, have also recognized that this type of production control could be used much more frequently and in other workshop areas, if the required planning data were made available more easily. This can make a big difference, especially in production cells that are resources that support many value streams, but also processes that have short cycle times. To make the scheduling even better and more reliable, more exact data is needed and not only assumptions and standard times. This can be accomplished by logging production data to get actual cycle times, availability, quality yield etc. for each product and operation.

The paper describes how the required information infrastructure has been designed and how it can be combined with this novel type of optimized adaptive planning to achieve a significant improvement in production efficiency. The solution is a based on a system architecture and information infrastructure with a middleware that provides a specific production cell with all the relevant planning data. These data include information about where the products are in the production cell as well as the rest of the flow; the status of these products, and its influence on the content and characteristics of the upcoming processes; and the condition of the production equipment. The work reported in this paper are results from two research projects; an EU project under the H2020 and Swedish national funding.


378. How to support storage process in dismantling facility with IT solutions? – case study

Izabela Kudelska, Monika Kosacka, Karolina Werner- Lewandowska

Poznan Univeristy of Technology, Poland

Warehousing becomes one of the most important process carried out in the disassembling facility. Legal requirements, company’s limitations in terms of resources (space, people, money) and a variety of storage parts (different size, lack of standards), cause many problems in the warehouse process. Efficiency of warehousing becomes increasingly important due to the the need to find new opportunities for growth of competitive advantage for dismantling station. The aim of the work is to develop the concept of an IT tool supporting decision-making process related to the parts allocation in the warehouse on the example of selected disassembly station in Poland. Classification of parts and their proper storage will contribute benefits in the context of implementing the concept of sustainable development in practice. Article has got a demonstrative-concept character with elements of a case study.


358. BigBench workload executed by using Apache Flink

Sonia Bergamaschi, Luca Gagliardelli, Giovanni Simonini, Song Zhu

Università di Modena e Reggio Emilia, Italy

Many of the challenges that have to be faced in Industry 4.0 involve the management and analysis of huge amount of data (e.g. sensor data management and machine-fault prediction in industrial manufacturing, web-logs analysis in e-commerce). To handle the so-called Big Data management and analysis, a plethora of frameworks has been proposed in the last decade. Many of them are focusing on the parallel processing paradigm, such as MapReduce, Apache Hive, Apache Flink. However, in this jungle of frameworks, the performance evaluation of these technologies is not a trivial task, and strictly depends on the application requirements. The scope of this paper is to compare two of the most employed and promising frameworks to manage big data: Apache Flink and Apache Hive, which are general purpose distributed platforms under the umbrella of the Apache Software Foundation. To evaluate these two frameworks we use the benchmark BigBench, developed for Apache Hive. We re-implemented the most significant queries of Apache Hive BigBench to make them work on Apache Flink, in order to be able to compare the results of the same queries executed on both frameworks. Our results show that Apache Flink, if it is configured well, is able to outperform Apache Hive.


32. Smart Data Hub: Retrofit solution to acquire process-inherent knowledge

Dennis Cüneyt Bakir, Tobias Feickert, Robin Bakir

Innovator_Institut, Germany

Within the full paper, we will learn how a profound understanding of complex (and up to now) not assessable data ensures more resource-efficient production processes. Focal point is the description of the development of the now existing retrofit-solution, named Smart Data Hub (SDA). This industry integration devices serves as easy to use enabler for smart production, even in overaged production systems. Furthermore, it is quite handy and able to communicate with almost every existing sensor through a unique addressing option.

The validation is based on an industry-driven problem regarding blow mould production of plastic goods. So far existing and comparable solutions imply a cost relationship of about 1:750 and delivery a sample rate of 1:0.05. So, the SDA is more cost-efficient, delivers a higher accuracy and sample frequency and does not imply a tremendous IT-architecture, which makes it predestined as industry 4.0 enabler for SME.

The SDA, which serves as an add-on device bound to or inserted into the mould-tool itself, was first used in the terms of assessing data from of the specific internal conditions of closed overpressure mould processes. So, corresponding to each product, the ideal temperature and pressure conditions, in form of specific recipe, were conducted. Overlong cycle times of the production process itself were trimmed by more than 17,5%, without a loss in terms of product quality.

 
4:30pm - 5:50pmSES 7.5: Smart Factories and Industrial IoT
Session Chair: Americo Lopes Azevedo
Aula Q (first floor) 
 

319. Development of IOT-based Reconfigurable Manufacturing System to solve Reconfiguration Planning Problem

Kezia Amanda Kurniadi, Kwangyeol Ryu

Pusan National University, Korea, Republic of (South Korea)

Reconfigurable Manufacturing System (RMS) appeared as a solution to high variation in customer demands allowing manufacturers to satisfy different amount of demands in each single period. In RMS, the system satisfies demands by reconfiguring the machines exactly when and where needed by adding and removing machines whose number depends on the demand of every single period. The reconfiguration process brings a critical issue within the RMS that is called as reconfiguration planning problem (RPP) in this paper. However, with the rise of Internet of Things (IoT) that has been a global issue, many companies and manufacturers are trying to integrate it into their smart systems. RMS as well needs to apply IoT in order to establish the internetworking between machines and the logic, so that RPP can be solved, automated, and controlled. This paper addresses the importance of the integration of IoT into RMS and presents the development of mathematical model to solve RPP in order to save reconfiguration time, cost, and effort. The result of the proposed idea is validated by using simulation software.


17. Benchmarking of tools for User eXperience analysis in Industry 4.0

Margherita Peruzzini, Fabio Grandi, Marcello Pellicciari

University of Modena and Reggio Emilia, Italy

Industry 4.0 paradigm is based on systems communication and cooperation with each other and with humans in real time to improve process performances in terms of productivity, security, energy efficiency, and cost. Although industrial processes are more and more automated, human performance is still the main responsible for product quality and factory productivity. In this context, understanding how workers interact with production systems and how they experience the factory environment is fundamental to properly model the human interaction and optimize the processes. This research investigates the available technologies to monitor the user experience (UX) and defines a set of tools to be applied in the Industry 4.0 scenario to assure the workers’ wellbeing, safety and satisfaction and improve the overall factory performance.


306. An application of Industry 4.0 to the production of packaging films

Pierpaolo Caricato, Antonio Grieco

Università del Salento, Italy

The “Piano Nazionale Industria 4.0”, the Italian plan for the adoption of the Industry 4.0 paradigm by the Italian manufacturing system, indicates a set of enabling technologies that must be used to be able to achieve the rewards that such paradigm promises. Advanced manufacturing solutions and Big Data and analytics are among them. 

We present an application of these enabling technologies to the production of packing films, showing the results of the application of such techniques to a real case in this sector.

The production planning issues that are addressed often include contrasting objectives and strategies: on one hand the legitimate requirement to provide the customers with an effective service, on the other hand the need to efficiently use the production capacity. These two drivers often lead to opposite directions when a decision must be taken.

The usage of the presented Advanced Planning and Scheduling (APS) tool allows the decision maker to rapidly generate a wide range of different scenarios for the production planning problem at hand, that are obtained automatically varying the weight of the different drivers defined by the user. The vast amount of different results is then analyzed and presented to the decision maker, using advanced data analytics techniques in order to put him/her in the condition to rapidly take an aware and solidly supported decision.

We introduce the main aspects of the production planning addressed by the presented tool, with an insight in the artificial intelligence techniques used to represent its constraints and its objectives. We then show how different scenarios can be built for the same problem by varying the importance given to the main defined strategies, namely: meeting the customers’ deadlines, efficiently using the available production capacity, minimizing the stock costs. Finally, we illustrate how the usage of an effective and reasonably compact representation of the results can rapidly allow the user to take conscious decisions that lead to a well-balanced trade-off between the pursued contrasting objectives.


203. An Industry 4.0 case study in fashion manufacturing

Antonio Grieco1, Pierpaolo Caricato1, Doriana Gianfreda1, Matteo Pesce2, Valeria Rigon2, Luca Tregnaghi2, Adriano Voglino2

1Università del Salento, Italy; 2Bottega Veneta srl, Montebello Vicentino (VI), Italy

The “Piano Nazionale Industria 4.0”, the Italian plan for the adoption of the Industry 4.0 paradigm by the Italian manufacturing system, indicates a set of enabling technologies that must be used to be able to achieve the rewards that such paradigm promises. Advanced manufacturing solutions, simulation, horizontal/vertical integration and Big Data and analytics are among them.

We present an application of these enabling technologies to Bottega Veneta, an Italian luxury goods house renowned in the world for its leather goods. In particular, we address the production process, which is distributed across several elements of the supply chain and the relative the management issues.

We show how the integration among the different entities in the supply chain and the interoperability of systems within each entity leads to the availability of a large set of data and information, that can be effectively used to feed data analytics systems such as decision support systems. These data are hence processed with advanced tools (analytics and algorithms) to generate meaningful information.

The Bottega Veneta supply chain includes: the main firm, controlled factories and several independent producers, which provide the ability to perform specific parts of the production process. The “as is” production management is conducted using different systems: an ERP system for the main firm, a vertical ERP solution tailored for fashion companies in the factories, an APS (Advanced Planning and Scheduling) tool to provide plans for the factories. The integration among the systems is achieved through traditional data exchange tools. The traditional ERP processes customers’ orders data to feed the APS, which provides its processed results in terms of due dates and production orders to the factories’ vertical ERPs. Independent producers are individually managed outside these systems.

We propose an Industry 4.0 inspired framework as an evolution of the current situation, introducing a uniform data model, used by all the actors involved in the production process. This model is used to collect and represent the large amount of data that are involved in the production process, including logistic information such as due dates and customers’ data, production details such as production cycles, technological constraints and feedback data from the floor shop.

The continuously collected data are both used to effectively coordinate the different actors in the supply-chain as well as within each factory and to feed a complex analytics system that includes, among the other, visual representations of the data that are meaningful to the proper user and a DSS (Decision Support System) that allows production planner at different levels to focus on different automatically generated and locally optimized scenarios to support them in taking better decisions. A specific insight in the algorithms and mathematical models used by the DSS is also presented.

 
4:30pm - 5:50pmSES 7.6: Product and Process Design
Session Chair: Luca Di Angelo
Aula R (first floor) 
 

39. Redesigning barrier mechanism for railway applications

Gonçalo Marques, Fra Silva

ISEP - Instituto Superior de Engenharia do Porto, Portugal

For a long time that barriers mechanisms applied in the railway environment are common, having always as main concern ensuring the functional safety of its use. To achieve this, techniques with great technology maturity have always been used in barriers systems. As a result, these devices have always presented a high cost and long life cycle, when compared with similar used in other types of applications. This life cycle lengthening is today reaching the end, presenting problems on its components due to equipment obsolescence.

This project was carried out in an industrial environment at EFACEC – Engenharia e Sistemas, Transports department, located in Maia – Portugal. In this project it was applied an innovative approach to this type of equipment and components. The work started by a full analysis of the actual mechanism components, corresponding manufacturing processes and usual problems. With Value Analysis methodology, it was possible to identify critical components, regarding both the value in the mechanism and their obsolescence. Based on this analysis, novel solutions were proposed aiming to change the state of the art solution for the Level Crossing barrier mechanism, always ensuring the safe fail mode.

The materials and components have been selected and designed in order to solve all the current problems, being functional and reducing the cost when compared to the current mechanism.


315. Comparison of commonly used sail cloths through photogrammetric acquisitions, experimental tests and numerical aerodynamic simulations

Michele Calì1, Salvatore Massimo Oliveri1, Antonio Gloria2, Massimo Martorelli3, Domenico Speranza4

1University of Catania, Italy; 2Institute of Polymers, Composites and Biomaterials , National Research Council of Italy, V.le J.F. Kennedy 54 – Mostra d’Oltremare PAD.20, 80125 Naples – Italy.; 3Department of Industrial Engineering, University of Napoli Federico II, P.le Tecchio, 80 - 80125 Napoli – Italy; 4Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio, 43 - 03043 Cassino (Fr) - Italy

Sail manufacture has undergone significant development due to their implementation and increased application in such sailing races as America’s Cup and the Volvo Around-The-World Race. These competitions require advanced technologies to improve sail performance. Hull design is fundamentally important but sails, i.e. the only propulsion instrument, play the key role in boat dynamics. Under aerodynamic loads, sail cloth deforms, aerodynamic interaction is modified and the pressure on the sails is unevenly distributed resulting in performance inconsistencies.

Interaction between fluid and structure requires a solution which can combine both aerodynamic and structural numerical simulations. Furthermore, the aeroelastic sail characteristics must be applied accurately in numerical simulations as they have profound impact on the dynamic performance of the sail. Only precise knowledge of the constituent materials provides precise numerical simulations.

Elastic orthotropic characteristics must be obtained by experimental testing. They depend on the fibre orientation (weft and warp) of the sail components cut by the sail maker’s plotter and then sewn together to form the sail. Sail thickness varies where reinforcements are added to support areas subjected to greater strain, e.g. in the pockets of cloth sewn or glued onto the sail where the reinforcement spars are inserted.

In particular, the present paper evaluates the impact that the distribution of fibres and the geometric arrangement of sail cloth have on sail dynamic performance in terms of pressure, vibration and dissipated energy. Digital photogrammetry is used to acquire figures, undertake the 3D reconstruction of sails and validate the structural and CFD numerical model.

Photogrammetry markers positioned on the surface and on sail structures are acquired by means of drones, whereas the 3D reconstruction of the sails is undertaken both in static conditions and during navigation.

Conforming to UNI EN ISO 13934-1, 2000, experimental sail characterization was performed using an Zwick & Roell Z100 tensile testing machine. In particular, tensile tests in weft and warp directions were performed on eleven different types of sail cloth. Subsequently, the elastic modulus and stress-strain curve were evaluated. The sail was modelled with Detached Eddy Simulations (DES), providing drawings of the topology of turbulent structures in the sail wake and revealed new flow features. As expected also in industry 4.0 the method allows to control the production process and final product optimization.


48. Optimising a specific tool for electrical terminals crimping process

Tiago A. M. Castro, Francisco J. G. Silva, Raul D. S. G. Campilho

Instituto Superior de Engenharia do Porto, Portugal

The continuous need for increasing productivity leads to the use of increasingly sophisticated equipment, enabling new approach techniques of manufacturing processes, higher speeds and greater accuracy in the final product. However, almost all of the equipment require appropriate tools, which effectively take advantage of their available potential. Engineering has an extremely important role in this matter since it will have to develop the tools regarding the satisfaction of a large number of requirements. This work was developed around a real need, having been stipulated the requirements needed by the customer, being the tool design elaborated around these same requirements. A tool optimisation was undertaken still at the preliminary draft stage, the materials have been carefully selected and the budgeting was also presented, as well as a plan for the operation and maintenance of the tool.


65. Investigation on the industrial design approach for CNC machine tools and its implementation and application perspectives

Xihui Yang1,2, Kai Cheng1

1Brunel University London, United Kingdom; 2School of Mechano-Electronic Engineering, Xi’dian University, Xian, P.R. China

Industrial design for CNC machine tools is becoming increasingly important, although it has more technological and usage complexity compared with consumer electronic products and ICT devices. This paper presents the development of an industrial design approach for CNC machine tools and its implementation perspectives in the advanced mechatronic and CNC machine application contexts. Firstly, the investigation is focused on the industrial design ideas for CNC machine tools by formulating the advanced design concepts, ergonomics and human-machine interactions, and the importance of user experience of CNC machines. Then, the industrial design principles for CNC machine tools are discussed particularly concerned with the machine configuration, geometrical shape/form, colour, digital enhancement, human-machine interaction, and the machine design services. Furthermore, the industrial design approach is proposed with application case studies on design of specific CNC machines. Finally, the implementation of the approach is demonstrated through the development of virtual machine tools at Brunel University London. The paper is concluded with further discussion on the potential and application of the industrial design approach for CNC machines broadly.

 
6:00pm - 7:00pmGuided Tour of Modena Downtown
Departure from San Geminiano (conference venue). Tour will end at Caffetteria Giusti
Modena city center 
7:30pm - 8:30pmAperitif
and Free Night
Via Farini, 83 - Modena
Modena guided tour will end here
Caffetteria Giusti 
Date: Thursday, 29/Jun/2017
8:30am - 9:00amRegistration & Welcome Coffee
Complesso San Geminiano 
9:00am - 10:00amSES 8.1: Permeating lean thinking into value networks: an Asian perspective
Session Chair: Koichi Murata
Aula Convegni (first floor) 
 

320. On Stability of Supply Performance by Work-In-Progress Management: A Case Analysis of Photovoltaics-based Electricity Supply System with Storage Batteries

Tetsuya Sato1, Koichi Murata2, Hiroshi Katayama1

1Waseda University, Japan; 2College of Industrial Technology, Nihon University, 1-2-1 Izumi-cho, Narashino, Chiba 275-8575, Japan

For many years, supply performance of goods to demand sites has been analysed, designed and improved by various ways such as Heijunka (load-levelling) concept and methodology. Basic structure of this approach is, in general, to adapt demand speed and fluctuation by managing work-in-progress (WIP). Meanwhile, energy loss reduction in electricity supply operations contributes to serviceability of electric power industry that consists of supply stability, cost rationality, resource savings etc. Furthermore, to expand renewable energy sources in the total energy consumption is a social trend for increasing energy self-sufficiency and reducing environmental load, but on the other hand the introduction of renewable energies involves challenges such as unstable output, high costs and installation constraints. For solving these problems, introduction of the smart-grid platform, which is an interconnected electricity network with power conditioning, production control and distribution management functions, is advocated in recent years. This research, taking electricity supply operations on the microgrid (semi self-contained smart-grid) platform using photovoltaic generation as the objective system, examines its performance for identifying the way to stable supply by WIP managing model. Performance analysis is examined by simulation experiments with the proposed model and obtained results suggest that Heijunka of power supply into the microgrid is realised in time-domain by the storage batteries. Moreover, the proposed model reveals optimal parameters of the entire system to each interconnected household, such as number of the photovoltaic generator units and capacity of storage batteries.


327. Legend and Future Horizon of Lean Concept and Technology

Hiroshi Katayama

Waseda University, Japan

Back to 1990, “The Machine that Changed the World” was published, which is one bestselling book on the way of manufacturing businesses that was named “lean production” in this book. It stressed the distinctive feature of the way of management of Japanese car industry, however, described feature is not necessarily Japanese car industry but also other manufacturing industries in Japan including almost all fabrication and process industries. Lean management, of which shop floor version is lean production, is actually a tradition of Japanese way of organizational management. Original concept can be recognized in Japanese turbulent period in 15th to 16th century. Typical example is “Akazonae: A type of military unit used in feudal Japan” that means Red Colour-armed Soldiers originated by Takeda warriors and Sanada warriors. The key point of this concept is fighting with an indomitable spirit and it is inherited to the concept of making unremitting efforts for business called “contradiction-driven approach” as the key concept of lean management. From early Meiji era (1868-), Japanese newly established civilian government conducts to creating industrialised society and encouraging to catch up related technology from mainly western countries. In early Showa era (1926-), industrialization has been took off gradually including establishment of Toyota Motor Co., Ltd., and many relevant methods contributing productivity have been developed and transferred among industries. Conceptual legends are i.e. Muri (Strain), Mura (Variegate), Muda (Waste) and Plan, Do, Check and Action Cycle (PDCA). Nowadays, all of these words are well known among industrial professionals and concerned academicians over the world. Based on the above issues, this paper tries to figure out historical trend with remarkable milestones and future horizon of the essential concept and technologies of lean management. These includes white box vs. black box approaches, proactive vs. reactive operations and similarity-based model analysis. (297 Words)


364. Measuring Efficiency and Creativity of NPD quoted by QFD

Koichi Murata

Nihon University, Japan

This paper analyzes a process of new product development (NPD). For the analysis, one analysis method and two indexes to measure NPD performance are proposed. The analysis method quoted by quality function deployment (QFD) matrix is developed to clarify a state transition of NPD process, which are from an extraction of customer needs to a design of product specification. Two indexes measure efficiency and creativity in the focused process. As the analysis result of three NPD cases with the collaborative company in Japan, various types of NPD are confirmed from the viewpoint of the two indexes. Proposed framework to consider new product concept is also constructed for becoming useful for future NPD.

 
9:00am - 10:00amSES 8.2: Robotics and Computer Integrated Manufacturing
Session Chair: Giovanni Berselli
Aula N (first floor) 
 

38. Designing a robotic welding cell for bus body frame using a sustainable way

André Filipe Castro1, Manuel F. S. Silva1,2, Francisco J. G. Silva1

1Instituto Superior de Engenharia do Porto, Portugal; 2INESC TEC, Rua Dr. Roberto Frias, 4200 - 465 Porto, Portugal

The implementation of automatic systems to execute tasks on the automotive industry brings many advantages when compared to humans. Although the increased productivity is a significant improvement, it is not the main reason to replace humans for autonomous systems. The quality and reliability emerge as important advantages in the use of automatic systems. Since safety became the number one priority of European standards, the quality factor has an enormous importance in the automotive industry.

Besides the most common vehicles which are mass produced by the largest automotive groups, special vehicles, such as buses, ambulances and garbage trucks among others, circulate daily on the roads around the world. These types of vehicles are produced by smaller companies that are specialized in a certain genre of vehicles.

The small quantities of the production series and the high rate of customization per client make it impossible to use fully automated production lines. However, the legal requirements to produce these vehicles specify dimensional accuracies and quality grades that are becoming harder to achieve with human workers. These companies are finding the solution for this problem by using flexible manufacturing cells that are able to execute the most critical tasks.

This study aimed to determine the advantages of using a robotic welding cell to produce bus body structures and to follow its implementation in the production process. In order to make a reliable data comparison, it is chosen a part from the bus’s luggage to execute all necessary tests. Furthermore, the use of a robot out of service was also studied because the robot already owned presents the characteristics needed for this kind of service, allowing an enhancement of the project performance and ensuring the reusability and life-extend of some important and expansive tools.

The method includes the development of a software simulation, one test using the robotic cell and ten tests using a human worker. The cycle time measured by the robotic cell is considered as a constant and the cycle time for a human worker is given by the average of the ten measures. The setup time is not considered for this study due to the possibility of using the same jigs for both tests. The test pieces are evaluated recurring to non-destructive and destructive tests to gather information about the quality of the welded joint: porosity, penetration and finishing.

At the end of this study, a significant reduction on the time needed to produce one component was achieved, as well as significant improvement on the product’s quality. The reduced cycle time brings an economical benefit: lower cost of manufacturing and higher profits allows the company to evolve into new markets and clients. The reduction is expected to be significant, allowing for a quick payback of the investment. The quality improvement is achieved by the highly precise manufacturing process, which is possible due to the robotic control. This key advantage enhances the company's competitiveness and makes possible to fulfill the increasingly demanding European standards.


198. Opportunities for robotic automation in wood product industries: The supplier and system integrators´ perspective

Steffen Andreas Landscheidt1, Mirka Kans2, Mats Winroth3

1Linnaeus University, Sweden; 2Department of Mechanical Engineering, Linnaeus University, Lückligs plats 1, 351 95 Växjö, Sweden; 3Technology Management and Economics, Chalmers University of Technology, Vera Sandbergs Allé 8, 412 96, Gotheburg, Sweden

In many industries, the automation of manufacturing processes is seen as an appropriate way to stay competitive, to increase market shares or to avoid outsourcing to low-cost countries. This is often achieved by the implementation of flexible manufacturing systems such as industrial robots. However, in industries with low or even no experience of the utilization of automation, discrepancy between what is requested by a company and what is actually the best way and feasible to fulfill these demands, could be observed. Company leaders are often interested in automating the most complicated processes in their production, making an automation project hardly performable and practical. This phenomenon can be witnessed when attempting to copy successful automation projects from other industry sectors to industries with little to no experience of automation such as wood product industries without understanding crucial underlying factors such as programming time and cost, additional equipment or the personnel´s competence. In many cases this can result in poor experiences and lost trust in new technologies. Understanding and acquiring knowledge about vital automation factors from an automation perspective are therefore important for wood product industries in order to achieve successful automation.

In this qualitative research, several sales engineers of robot manufactures and robot system integrators were interviewed to gain insight into possibilities, opportunities and applications for robotic automation of different wood product industries. Thematic and content analysis of the interview data was conducted as part of the data for gaining relevant results.

Results indicate that system integrators and robot manufactures do not see any technical or material based hinders for wood product industries to automate. However, opinions about what and how to automate differ a lot. In wood product industries the complex and complicated tasks are prioritized with respect to automation, while system integrators tend to start with simple applications in order to get a solid start. As one of the reasons for this discrepancy, the lack of experience of utilizing automation equipment by production managers in wood product industries is identified. Often, they are not aware of their possibilities and opportunities where and when to gain the biggest production improvements, both for worker´s workload and for production efficiency. In addition, the benefits of using flexible industrial robots in production systems will be discussed.


264. New Motion Control approach for synchronized handling of complex parts

Julio Garrido Campos, David Santos Esterán, Juan Sáez López, José Ignacio Armesto Quiroga

Vigo University, Spain

Machinery for parts manipulation (picking, pick to place, etc.) is one of the most demanded processes in many industry sectors, from agroalimentary to industrial manufacturing. Among these types of processes, one of the most in demanded is the separation and individualization of parts of a bulk set in order to place each one into separated containers.

At present, the picking problem is solved with different technologies. Handling not a problem if parts have fixed forms and fixed mechanical properties, which facilitates their manipulation with vacuum suction pads or specifically designed clamps. These elements are often installed in robots (delta robot, cartesian robots, anthropomorphic robots, etc.). The most common industry solution is the use of Delta robots driven by artificial vision systems to detect the position of incoming parts. These positions are continuously recalculated as the parts transportation system moves-as this movement is sensed by encoders.

However, heteromorphic pieces are difficult to grasp by clamps, and vacuum suction is not suitable in the case of specific product properties: slippery parts, soft parts, frozen parts, etc. Sometimes, a high cadence of parts make unsuitable solutions based on the use of delta robots. For these, mechanical pushers or blower can be used. But it is not possible to get a precision part positing by pushing and blowing when working fast, and especially when dealing with sleepy parts (as frozen, oiled ones) since is not possible to accurately predict the final speed or position.

Therefore, push or blow cannot be used when working with sliding products and parts (position parts) have to be synchronize with a second output line. Sometimes, to get that synchronism, successive belts at different speeds, which are slowed and accelerated are used. The drawback is the sliding of the pieces and the cadence.

None of the mentioned methods allow the synchronous positioning with products with complex morphological and dynamic characteristics. This paper addresses this problem. The paper proposes a new handling methodology based in a double strategy. First, the clamping of the piece by adjusting two controlled barriers to part dimensions, to later proceed to a part translation by push and/or retention, to be able to deposit the part in a output line in a synchronous way.

The paper presents the mechanical and control principles of the proposed new manipulation method. The control algorithm is described. It uses standard motion control blocks (MC_PLCOpen), although there is no block that solves the proposed functionality by itself, so a new one is developed. Moreover, a prototype implementation and the experiments results are presented. Finally, taking into account the requirements of a typical industrial application, the functional viability of the new system is analyzed.

 
9:00am - 10:00amSES 8.3: Smart Factories and Industrial IoT
Session Chair: Dusan Sormaz
Aula O (first floor) 
 

105. Simulation based Validation of Effects through ICT enabled Real-Time-Capability in Production Planning: an Example from Engineer-to-Order Plant Building Industry

Patrick Dallasega1, Rafael A. Rojas C.1, Erwin Rauch1, Dominik T. Matt1,2

1Free University of Bolzano, Italy; 2Fraunhofer Italia Research s.c.a.r.l., Innovation Engineering Center (IEC), via Macello 57, Bolzano, 391

With the actual trend towards Industry 4.0, new technologies will provide the digitalization of general data and make it available in real-time and worldwide through the Internet. Information, in the specific, becomes the new gold for the smart and digital factory of the future. Especially in production planning and control, a real-time decision-making capability represents high potentials for optimizations along the whole supply chain. Moreover, the ability modeling the behavior of those systems endows decision-makers with forecasting possibilities. In this paper, a simulation-based approach is presented to validate and verify the effects of an ICT-enabled and nearly real time capable production planning approach. The approach has been applied in an example from Engineer-to-Order (ETO) plant building industry, where engineering elaborates the technical design, fabrication produces the components and installation teams perform the final assembly on-site. Traditionally production planning is centralized following a master schedule that rarely is up to date, ignoring deviations on-site. As a result, components are manufactured and delivered in advance creating non-value adding activities and inventory levels. Furthermore, if production planning is based on not current data, the priority in order-release at the fabrication shop is not optimized for a Just-in-Time delivery on-site. Thus, in this paper, we propose a decentralized and ICT-supported near real-time capable production planning approach.


333. Trustworthiness Requirements for Manufacturing Cyber-Physical Systems

Radu Babiceanu, Remzi Seker

Embry-Riddle Aeronautical University, United States of America

Distributed manufacturing operations include cyber-physical systems vulnerable to cyber-attacks. Long time not considered a priority, cybersecurity jumped to the forefront of manufacturing concerns due to the need to network together legacy, newer equipment, and entire operation centers. This paper proposes trustworthiness solutions for integrated manufacturing physical-cyber worlds, where trustworthiness is defined to complement system dependability requirements with cybersecurity requirements, such that the resulting manufacturing cyber-physical system delivers services that can justifiably be trusted. Acknowledging the inevitability of cyber-attacks, the paper models the cybersecurity component using the resilient systems framework, where system resilience is viewed as preservation of a required state of cybersecurity.


254. Virtual commissioning of camera-based quality assurance systems for mixed model assembly lines

Nils Piero1, Michael Schmitt2

1GSaME Uni Stuttgart, Germany; 2Fraunhofer Institute for Computer Graphics Research IGD, 64283 Darmstadt, Germany

Mixed model assembly lines are subject to increasing complexity due to increasing variants variety per assembly line, short product life cycles and increased product complexity. Especially in the automotive production the integration of new variants and segregation of discontinued variants in short intervals lead to constant change in mixed model assembly lines. The demand for high-quality products compels the quality assurance to provide methods that meet these changing requirements.

Existing methods of quality assurance usually answer the questions to completeness, correct component variants and correct position of mounted components based on simple image processing techniques. Real images are compared to reference images in order to perform a binary classification of individual test features. The required reference images are extracted from real images. Those methods can only be applied when the production of a new model has been running for some time and extensive manual teaching processes have been completed. Quality assuring systems should be able to meet these changes and be in action for early phases in the product ramp-up. Thus, possible production errors can be detected early and countermeasures can be initiated.

We propose a new Computer Vision based technique to ensure the quality of the automotive aggregate assembly. It uses CAD Data that is already available from the product planning phase to check all product variants on the assembly line for misplaced or wrong components. One does not need to collect data from real images to teach the decision making algorithm. This solution can hence be used already in the ramp-up phase.

Our method can also easily adapt to changes of production, where existing methods need to redo the whole teaching process, we just need to set the new nominal position of the part in the reference coordinate system. This can even be done semi automatically and synchronously with the changes in the assembly line.

 
9:00am - 10:00amSES 8.4: Risk Management
Session Chair: Chike F Oduoza
Aula P (first floor) 
 

307. Framework for Risk Management Software System for SMEs in the Engineering Construction Sector

Chike F Oduoza, Nengi Odimabo, Alexios Tamparopoulos

UNIVERSITY OF WOLVERHAMPTON, United Kingdom

Small and medium-sized enterprises (SMEs) especially in the construction sector are vulnerable, and face daily exposure to a wide variety of business risks whilst they operate without a risk management system in place. There is abundant evidence both from informal market research and industry surveys to confirm that SMEs are continuously handicapped and therefore underperforming due to their inability to manage operational risk challenges facing them on a daily basis. The objective of this study is to develop a risk management software system which will enable SMEs in the construction sector to proactively identify, analyse and manage the large variety of risks facing them to enhance business performance. In the construction sector performance is assessed mainly in terms of time of completion, cost of project execution and overall quality of delivery.

The research methodology adopted in this study is underpinned by a framework based on the balanced score card which identifies a wide array of key risk indicators affecting performance in the construction sector. The user friendly risk management software system which is designed to accommodate various user levels guides the operator to avoid, minimise, mitigate or manage the relevant risks to enable successful performance outcome. The system designed and developed here will enable systematic risk management to achieve minimum cost and time overrun while optimising on quality of delivery in a project management environment.


304. Aspects of Risk Management Implementation for Industry 4.0

Jiri Tupa, Jan Simota, Frantisek Steiner

University of West Bohemia in Pilsen, Czech Republic

Industry 4.0 ordinarily called as “Digital Factory”, “Industrial Internet” or “Fourth Industrial Revolution” is comparatively new method of production processes management. In comparison to Industry 3.0, focused on the automation of single machines and processes, Industry 4.0 is focused on the introduction of Internet technologies into industry which is the main technical background. It is often understood as the application of the generic concept of cyber-physical systems to industrial production systems. Due to recently and higher interest of this topic, there are various definitions of Industry 4.0 which caused confusion rather than increasing transparency nowadays. In relation to risk management, resulting from new approaches, modified frameworks, more complex IT infrastructure and so on, new types of risks may occur. In many cases, the implementation of Industry 4.0 shown that connections of humans, systems and objects became more completive, dynamic and real-time optimized network. Through the use of technical approaches (for example cloud computing, cyber physical systems) as a key technology, all processes became more transparent and flexible. On the other hand there is a fact of data volume and availability enhancement in real time which causes new requests in infrastructure, management, technologies and so on. There are lot of smart and useful tools for risk management which were developed during previous Industry areas expansions. Therefore, the aim of this paper is to present result of research focus on related to key aspects and possibilities of risk management implementation to that Industry area.


5. Operational Hedging and Coordination in Prefabrication Construction Industry

Yue Zhai, George Huang

The University of Hong Kong, Hong Kong S.A.R. (China)

This paper explores a trade-off and coordination problem between two operational hedging methods in the prefabrication supply chain risk management. Operational hedging methods are adopted for mitigating the heavy impacts caused by potential risk in the prefabrication supply chain. Effects of two commonly used hedging strategies i.e. lead-time hedging and buffer space hedging are investigated in this prefabrication construction domain. These hedging methods though effective in improving system performance, however, add much pressure to the execution department, for extra investment would occur. In this way, under a decentralized system individual departments are not willing to take part in the hedging methods unless they could get better off. In this work, coordination mechanism that integrates these two hedging methods is investigated. This work focuses on the interface between a building company and a general contractor within a prefabrication construction industry. Specifically, the lead-time hedging which refers to reducing building lead-time uncertainties is adopted by the building company; and the buffer space hedging which refers to reserving more empty space than normal operation for flexible operation is conducted by the general contractor. We find that trading-off two hedging methods in a decentralized system outperformances the traditional model where only a single hedging methods is adopted , for the system profit get improved and each party gets better-off in the coordination mechanism. Besides, the hedging pressure is mitigated though the proposed mechanism. Later on, numerical studies are carried out to demonstrate the performance of the proposed model. We found that high building process uncertainty, high space congestion probability; and low unit hedging cost can be viewed as opportunities for both building company and general contractor to protect their profit by adopting the proposed coordination mechanisms. Furthermore, some more interesting managerial implications are obtained and summarized.

 
9:00am - 10:00amSES 8.5: Manufacturing Process and Technology
Session Chair: Dong-Won Kim
Aula Q (first floor) 
 

196. Assessment of Commonly Used Tool Life Models in Metal Cutting

Daniel Johansson1, Sören Hägglund2, Volodymyr Bushlya1, Jan-Eric Ståhl1

1Lund University, Sweden; 2Assessment of Commonly Used Tool

The ability to predict and model tool wear and excepted tool life in metal cutting is of great importance to secure robust, predictable and stabile manufacturing systems. Tool life models are used by tool manufactures to assist end users with optimal cutting data published in catalogues or online web assistance applications. A model dependent on cutting speed, depth of cut, feed and tool geometry describing the expected time the tool can be engaged with the work piece material producing parts within a given quality is needed. As tool manufactures are moving toward not only supplying tool inserts but also increasingly supporting the end user with cutting data recommendations and optimal tool solutions with online software, tool life modelling is becoming more important. The cost and environmental impact of collecting tool life data for an increasing amount of tool material, tool geometry and workpiece combinations calls for a generic tool life model that can handle this complexity in a cost efficient way.

A number of tool life models have been presented in literature over the last century but little effort has been made in judging their reliability. In this work, eleven different combinations of work piece materials and tool grades have been evaluated in wear test when turning with cemented carbide inserts. The most commonly used tool life models such as the Taylor model, the Extended Taylor model, the Coromant Turning model version 1 and the Colding model have been tested on the data and their accuracy is presented.

The different Taylor models are relatively accurate when used with caution and in smaller ranges of selected chip thickness. All models preform most accurate when using the Woxén equivalent chip thickness as base for the tool life model. When extended Taylor is used, it produces more accurate results when using equivalent chip thickness then when based on feed and depth of cut even though a fourth constant is introduced in the latter.

The traditional Taylor tool life model models the tool life with an average error of 17.9 %. The best preforming model is the Colding model which is most accurate in nine out of eleven combinations and has the lowest model error with an average model error of 4.0 %.


8. Too sharp for its own good – Tool edge deformation mechanisms in the initial stages of metal cutting

Sampsa Vili Antero Laakso1,2, Tao Zhao2, Mathias Agmell2, Andrewk Hrechuk3, Jan-Eric Ståhl2

1Aalto University, Sweden; 2Lund University, Ole Römers Väg 1, 223 63, Lund, Sweden; 3Institute for Superhard Materials, 04074 Kiev, Ukraine

Metal cutting simulations have become an important part of cutting tool design and the research in the field in general. One of the most important aspects of modeling is the accuracy of the tool geometry. 3D microscopy is used for measuring the tool edge radius with good accuracy. However, especially with sharp tools, i.e. small tool edge radii, the measurements, no matter how accurate, are not much of a use, since the initial wear, or deformation is so fast in the first 1-30 seconds into the cutting, that the tool geometry is significantly different than the one measured from the new tool. The average tool life is often set to 15 minutes. Therefore, the cutting simulations that only predict the tool behavior in the first seconds of its lifetime are not very useful in predicting the process variables throughout the tool life. Simulations with creep and elastic-plastic material model however, can predict the initial deformation of the tool. This tool shape can be then used in rigid tool model to predict the process variables in the steady wear region of the tool life. This paper presents simulation model for predicting the initial tool edge deformation for WC-10%Co tool while machining AISI 304 stainless steel. The novelty in this approach is the simultaneous coupled calculation of contact surface temperature and stress and change of the tool shape.


153. Machinability of Cobalt-based and Cobalt Chromium Molybdenum Alloys - A Review

Hainol Akbar Zaman1, Safian Sharif2, Dong-Won Kim3, Mohd Hasbullah Idris2, Mohd Azlan Suhaimi2, Z. Tumurkhuyag3

1Chonbuk National University, Korea, Republic of (South Korea); 2Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia.; 3Department of Industrial and Information Systems Engineering, Chonbuk National University, Jeonju 561-756, Republic of Korea.

Cobalt chrome molybdenum alloy is considered as one of the advanced materials which is widely gaining popularity in various engineering and medical applications. However, it is categorized as difficult to machine material due to its unique combination of properties which include high strength, toughness, wear resistance and low thermal conductivity. These properties tend to hinder the machinability of this alloy which results in rapid tool wear and shorter tool life. This paper presents a general review of the materials’ characteristics and properties together with their machinability assessment under various machining conditions. The trend of machining and future researches on cobalt-based and cobalt chromium molybdenum alloys are also discussed.

 
9:00am - 10:00amSES 8.6: Digital Product and Process Development
Session Chair: Francesco Ferrise
Aula R (first floor) 
 

191. A Stereo-Panoramic Telepresence System for Construction Machine

Paolo Tripicchio1, Emanuele Ruffaldi1, Paolo Gasparello1, Shingo Eguchi2, Junya Kusuno2, Masaki Yamada2, Alfredo Argiolas3, Marta Niccolini3, Matteo Ragaglia3, Carlo Alberto Avizzano1

1Scuola Superiore Sant'Anna, Italy; 2R&D Unit, Yanmar Co. Ltd., Japan; 3Yanmar Research Europe, Viale Galileo, 55100 Firenze, Italy

Working machines in construction sites or emergency scenarios can operate in situations that can be dangerous to an operator such as direct control of the machine or teleoperation in co-presence. Remote operation has been typically hindered by limited sense of presence of the operator in the remote of the environment to due the reduced field of view of cameras. Starting from these consideration we are introducing a novel real-time panoramic telepresence system for construction machines. This system does allow fully immersive operations in critical scenarios while keeping the operator in a safe location at moderate distance from the construction site. An omnidirectional stereo vision head, mounted over the machine, acquires and streams data to the operator with a streaming technique that focuses on the current direction of site of the operator. According to the motion of the operator’s head, the telepresence system will determine the involved cameras to use and the appropriate region of interest in cameras. The operator uses a head-mounted display to experience the remote site also with the possibility to view digital information overlaid to the remote scene as a type of augmented reality. The paper addresses the design and architecture of the system starting from the vision system and then proceeding to the immersive visualization.


113. Semi-automatic Design for Disassembly strategy planning: an Augmented Reality approach

Francesco Osti, Alessandro Ceruti, Alfredo Liverani, Gianni Caligiana

University Of Bologna, Italy

The mounting issue of environmental care requires to apply better disassembly operations at the product’s End of Life. Planning and reckoning different disas-sembly strategies in the early stage design can improve the sustainable products conception. Nowadays many computer aided process planning software provide the optimized assembly or disassembly sequences, but they are mainly based on a time compression and cost compression approach. In this paper a novel method concerning design for disassembly is described and validated. An Augmented Reality environment has been implemented and modified integrating real human movements and virtual part unmounting in a mixed session. In such way, the op-erator may in a more natural and intuitive way test not only automatic disassem-bly sequences, but also different original strategies. The use of haptic devices guarantees more interaction with the 3D model than ordinary devices (mouse and keyboard). The method has been tested and compared with automatic optimiza-tion methods in order to demonstrate the improvements in disassembly strategy


221. VR-based Product Personalisation Process for Smart Products

Yuan Lin1, Shiqiang Yu1, Pai Zheng1, Liming Qiu2, Yuanbin Wang1, Xun Xu1

1University of Auckland, New Zealand; 2Department of Electrical and Computer Engineering, The University of Auckland, Building 902, 314-390 Khyber Pass Road, Newmarket, Auckland 1023, New Zealand

Through the synergies of advanced IT technologies in sensor network and hardware infrastructure, both industrial and consumer products are evolving rapidly to carry more smart features. To sharpen competitive edge in global market, manufacturers today ought to enable their customers to personalize their products to meet diversifying customer needs (CNs). However, the increasing complexity of smart product is dramatically expanding the design space due to over-loaded smart features, which results in significant challenges in the personalization of smart products. Typically, manufacturers operating in a configure-to-order (CTO) manner would adopt a mass customization strategy and implement it with a product configuration system (also known as product configurator). The user experience (UX) of personalizing products by conducting product configuration is crucial for encouraging customer retention and loyalty. This project studied the product personalization process for smart products by observing a group of customers conducting a series of product configuration tasks in several types of product configurators we developed for different platforms (web-based and Virtual Reality (VR) based version). By analyzing mental and physical reaction of the customer, a more systematic understanding of user preference has been attained. The proposed VR-based approach for realizing customer-centric product personalization has been proved to be valid and should be a valuable reference in the future development of the product configuration system.

 
10:00am - 10:55amKEY 5: Keynote Speech 5 (Kok-Meng LEE)
Physical Field-based Machine Perception for Intelligent Manufacturing
Aula Convegni (first floor) 
10:55am - 11:20amCoffee break
Gallery at first floor 
11:20am - 1:00pmSES 9.1: Robots in AVM
Session Chair: Rezia Molfino
Aula Convegni (first floor) 
 

278. The SwarmItFix pilot

Keerthi Sagar1, Luis De Leonardo1, Rezia Molfino1, Teresa Zielinska2, Cezary Zielinski3, Dimiter Zlatanov1, Matteo Zoppi1

1University of Genoa, Italy, Italy; 2Institute of Aeronautics and Applied Mechanics, Warsaw University of Technology, Warsaw 00-665, Poland; 3Institute of Control and Computation Engineering, Warsaw University of Technology, Warsaw 00-665, Poland

The paper presents the integration and experiments with a pilot cell including a traditional machine tool and an innovative robot-swarm cooperative conformable support for aircraft body panels. The pilot was installed and tested in the premises of the aircraft manufacturer Piaggio Aerospace in Italy. An original approach to the support of the panels is realized: robots with soft heads operate from below the panel; they move upward the panel where manufacturing is performed, removing the sagging under gravity and returning it to its nominal geometry; the spindle of a milling machine performs the machining from above.


106. AURA: An example of collaborative robot for Automotive and General Industry applications

Francesco Parodi, Gian Paolo Gerio

COMAU S.p.a., Italy

In June 2016, Comau presented at the Automatica fair in Munich, its flagship: the collaborative robot AURA.

AURA is the first collaborative robot with a payload higher than 100 kg. Its technology has been developed in close collaboration with some of the most titled Italian Universities in robotics field.

In particular, the technology is based on communication between the robot and a combination of sensors (used today for many Industry 4.0 devices) whose redundancy ensures the robot ISO certification.

Examples of applications ranging from the battery placement in the trunk of a luxury car (Maserati) to polishing an aesthetical front car body part. Switching to the General Industry, several cooperative mechanical components assembly/disassembly applications (such as various types of gearboxes) can be realized.

Referring to Industry 4.0, based on new programming methodologies, AURA has the possibility to be programmed easily by a Manual Guidance device, developed in collaboration with relevant external research partners support.

AURA can share the working area with the operator, reducing automatically the working speed to a collaborative speed for the man-machine collaboration when the human presence is detected. Depending on the application, the man can carry out different activities with AURA assistance: during handling operations the contact man machine takes place safely and without forced interruption of the working cycle.


163. The Robo-Partner EC Project: CRF activities and Automotive Scenarios

Giulio Vivo1, Alessandro Zanella1, Onder Tokcalar2, George Michalos3

1Centro Ricerche Fiat S.c.p.A., Italy; 2TOFAS, Buyukdere Cad Tofas Han 145 Kat 4-5 Zincirlik, 34394 Sisli Istanbul, Turkey; 3LMS, University of Patras,University Campus Rio Patras, 26500, Greece

Robo-Partner is a large scale integrated project (IP) co-funded by the European Commission, addressing “New hybrid production systems in advanced factory environments based on new human-robot interactive cooperation”. It includes 14 partners from 8 different European countries (Turkey, Italy, Spain, France, Greece, Luxemburg, Portugal, Germany), with the duration of 42 months; it is coordinated by TOFAS (the Turkish automaker based in Bursa) and LMS (the University of Patras, Greece). The project started its technical activities on November 2013 by introducing a hybrid solution involving the safe cooperation of operators with autonomous and adapting robotic systems through a user-friendly interaction. Centro Ricerche FIAT is contributing to the project with the application of the Human-Robot collaboration paradigm on some relevant test cases and automotive scenarios, reported in this paper with the purpose of disseminating the project achievements.


170. Criteria definition for the identification of HRC use cases in automotive manufacturing

Alessandro Zanella, Alessandro Cisi, Marco Costantino, Massimo Di Pardo, Giorgio Pasquettaz, Giulio Vivo

Centro Ricerche FIAT SCpA, Italy

Human Robot Collaboration is a rapidly emerging technology which is expected to have an important impact on future manufacturing design approach. The normative regulation was defined at the beginning of 2016 by the Technical Specification ISO/TS 15066 setting limits and methodologies for the safety in the workplace. The ISO standards are required for the proper design of the workplace and the cell, nevertheless the design and use of a HRC application in production has to be motivated by a proper benefit analysis. In facts, while currently many use cases are declared and tested, their identification process is often an experience based analysis.

The performed study aimed at the definition of a methodology for the objective identification of the most suitable applicative use cases for a profitable exploitation of HRC technology.

The analysis is based on the preliminary assignment of values to multiple Key Parameters (KPs). The KPs identification was based on a methodological analysis applied to multiple manufacturing cells in production. Core of the process was the identification of the criteria and the KPs.

A systematic application of the tool was made to test and fine-tune the developed methodology.

The paper wants to summarize the criteria and methodology that have been defined in the study.


138. Robotic AM system for plastic materials: tuning and on-line adjustment of process parameters

Paolo Magnoni1,2, Lara Rebaioli1, Irene Fassi1, Nicola Pedrocchi1, Lorenzo Molinari Tosatti1

1Consiglio Nazionale delle Ricerche, Italy; 2University of Brescia, Dep. of Mechanical and Industrial Engineering, via Branze 39, 25123 Brescia, Italy

The use of Additive Manufacturing (AM) techniques based on the extrusion of thermoplastic polymers, such as Fused Deposition Modeling (FDM), has increased significantly in recent years. Although AM allows the manufacture of customized and complex parts, the slow printing speed of standard AM systems limits their use for mass production. For this reason, a productivity improvement and an increment of achievable part size are key targets for future manufacturing systems.

Industrial extruders mounted on robotic manipulators allow a fused material deposition rate that is 10 to 20 times higher than the average deposition rate of commercial FDM systems. Moreover, AM system based on robotic platforms could replace some of the application functions of FDM printers providing more flexibility, better motion software support and an industrial level of reliability. Eventually, the use of plastic pellets instead of wires results in a cost reduction and a higher freedom in material selection.

Despite of these advantages, there are some drawbacks related to the manufacturing of big parts with high deposition rates, such as the irregular shape of deposited material in case of non-optimally tuned process parameters, which results in geometrical errors on the final part. Another critical issue is the material withdraw during the cooling phase, which could modify the deposited layer geometry.

In the present study, an industrial screw-based extruder has been modified and mounted on an anthropomorphic robot, realizing a flexible platform for the additive manufacturing of big objects. This work will address the aforementioned limitations proposing a method to find optimal values for relevant process parameters and a method for online monitoring and control of process state-variables, thanks to the integration of sensors into the robotic system.

In detail, in a first phase, a suitable experimental campaign has been developed according to Design of Experiments (DoE) in order to set the most important process parameters (extruder motor rotational speed, robot translation speed, layer height) ensuring a regular and constant deposited layer geometry. The relationship between the deposited track width and the aforementioned process parameters has been quantitatively studied by means of a statistical analysis of experimental results.

In a second phase, a closed-loop control has been implemented to further improve the process parameter setting based on data measured during the deposition process, in this way compensating the material withdraw or other unexpected defects. The laser triangulation sensor, which has been mounted on the extrusion head, has been used to measure the actual height of each layer. Based on the acquired data, the robot path has been corrected by the closed-loop control to guarantee a proper layer overlapping and, therefore, a regular built-up geometry.

A piece of furniture has been selected as representative case study of additive manufacturing of big parts and it has been manufactured to demonstrate the proposed procedure effectiveness.

 
11:20am - 1:00pmSES 9.2: Collaborative Robotics in Smart Manufacturing
Session Chair: Pedro Neto
Aula N (first floor) 
 

128. Towards shared autonomy for robotic tasks in manufacturing

Andreas Pichler, Sharath Chandra Akkaladevi, Markus Ikeda, Michael Hofmann, Matthias Plasch, Christian Wögerer, Gerald Fritz

Profactor GmbH, Austria

In recent years, the concept of robots cooperating with humans has gained a lot of interest, in both domestic and industrial areas. In industrial environments the combination of cognitive capabilities of humans with the physical strength and efficiency of the robots/machines can essentially reduce the amount of fixed production costs in relation to variable costs. The robot systems are also understood as proper mean to address changes in demography and shortage of skilled labor in material goods production. Furthermore, they provide higher flexibility for the automation and ensure durable quality of products which are already nowadays challenging companies.

Setting up and operating a system in a fenceless environment as well as being responsive to human interactions requires new sensor capabilities integrated in a human robot system. Such a flexible system has to be embedded in smart manufacturing system.

Human robot interaction is differentiated at different levels with varying degree of shared autonomy as human robot coexistence, cooperation and collaboration.

In this paper we will present a platform called XROB, which builds and utilizes models of human robot interactions in an intuitive way. Using this platform, the operator gets qualified to pursue different kind of task sharing operation in applications requiring customized patterns of interactions. According to the different kinds of shared autonomy we give examples of how processes can be implemented in industrial settings. The processes addresses key issues in manufacturing such as fast ramp up, zero defect inspection and increasing flexibility in the automation of assembly processes.

The coexistence scenario describes a robot assistant system focusing on quality control tasks. The mobile platform features a flexible quality inspection system which can be enhanced with a variety of sensors and inherits intuitive configuration capabilities. Working side by side in the same working space describes a scenario of an assembly of automotive combustion engines. Beside rapid reconfiguration of the system, also safety issues have to be taken into consideration. The assembly scenario demonstrates a cooperation scenario where robots carrying out screwing operations beside human attaching parts on the same work piece.

The third example shows the collaboration of human robot teams. The intense interaction between human and robot requires a mutual understanding of the task at hand. Specifically, for the robot to assist the human operator for a given task involves understanding the actions performed by the human, interpreting the activity and eventually interacting with the human. This is prerequisite to enable seamless interaction.

Finally, the paper sets the different levels of shared autonomy in comparison and gives remarks on the requirements of successful implementation in industry.


256. On Autonomous Robotic Cooperation Capabilities Within Factory and Logistic Scenarios

Giuseppe Casalino, Enrico Simetti, Francesco Wanderlingh, Kourosh Darvish, Barbara Bruno, Fulvio Mastrogiovanni

University of Genoa, Italy, Italy

The paper presents the development of a unified functional, algorithmic and Software (Sw) architecture, which can be adopted as a standard for controlling, at action level only, any robotic structure within a given wide class of them; even of reconfigurable type within the class; Such control architecture is therefore deemed very suitable for operating within factory and/or logistic, possibly reconfigurable, scenarios. Moreover, for the few cases of cooperative activities to be established between agents not allowed to be cable connected, an effective coordination policy, based on the exchange of a reduced information set, only regarding the cooperation goals, is developed; and relevant simulative and experimental trials are briefly outlined. Moreover, the advantage of having, in whatever operative condition, the possibility of commanding the involved structures only in terms of the ultimate goals of each action, also seems to be the right basis for having non-negligible improvements within their integration with automated action planning, and even learning, techniques.


190. Integration of a Skill-based Collaborative Mobile Robot in a Smart Cyber-Physical Environment

Rasmus Andersen1, Emil Blixt Hansen1, David Cerny1, Steffen Madsen1, Biranavan Pulendralingam1, Simon Bøgh2, Dimitrios Chrysostomou2

1Dept. of Mechanical and Manufacturing Engineering, Aalborg University, Fibigerstræde 16, Aalborg Øst, DK-9220, Denmark; 2Robotics & Automation Group, Dept. of Mechanical and Manufacturing Engineering, Aalborg University, Fibigerstræde 16, Aalborg Øst, DK- 9220, Denmark

The goal of this paper is to investigate the benefits of integrating collaborative robotic manipulators with autonomous mobile platforms for flexible part feeding processes in an Industry 4.0 production facility. The paper presents Little Helper 6 (LH6), consisting of a MiR100, UR5, a Robotiq 3-Finger Gripper and a task level software framework, called Skill Based System (SBS). The preliminary experiments performed with LH6, demonstrate that the capabilities of skill-based programming, 3D QR based calibration, part feeding, mapping and dynamic collision avoidance are successfully executed and strategies for further expansion of the operational capabilities of the system are discussed.


210. 3D metrology using a collaborative robot with a laser triangulation sensor

Gil Boyé De Sousa, Adel Olabi, Jorge Palos, Olivier Gibaru

Arts et Métiers ParisTech - Lille, France

Industrial robots are a key element in Smart Manufacturing systems. They can perform many different tasks such as assembly, pick-and-place, or even 3D metrology operations. In order to perform 3D metrology, the robot is equipped with a 2D laser triangulation sensor. The accuracy of the measurements made by this system is dependent of an accurate TCP (Tool Centre Point) calibration and the accuracy of the robot. In this paper, a TCP calibration method is applied to a collaborative robot. The hand-guiding feature of this kind of robots is used to establish a human-robot interaction to obtain the laser sensor TCP using a calibration sphere. Experimental results are presented to validate the procedure and evaluate the quality of the measurements.


92. Pose estimation and object tracking using 2D images

Fernando Casado García, Yago Luis Lapido, Diego P. Losada, Alejandro Santana-Alonso

AIMEN technology centre, Spain

Different factors are forcing the change in the logistics market, most notably e-commerce and manufacturing of custom-made products. Increasingly, customers look for personalized products and mass customization is pushing the industry to reduce time to market and to enhance production flexibility, where batch size tends to one. This fact is highly linked with warehouse management, where exploitation costs increase with the value-added tasks, where third party logistics (TPLs) must raise service quality while maintaining operating costs.

Thus, logistics is one of the most important links within the manufacturing chain. For this reason, automating intra logistic processes is a priority task to improve their performance. Goods are usually placed on pallets for transportation and stacking, so handling pallets becomes a necessity.

In this work, we present a detection system, based on 2D pattern recognition, for localizing and obtaining the pose of pallets in the working environment of autonomous mobile forklifts. The detection method is part of a novel automation solution designed to retrofit manual operated logistics vehicles, adding a new autonomous working mode. With this new working mode, the forklifts could be operated autonomously or in manual mode, obtaining a highly flexible pallet handling system that could be applied in shared spaces with humans.

We use two industrial HD cameras, one RGB installed on top of the forklift and one NIR installed between the forks. The detection system has two working modes, a) initial pallet identification and b) pallet tracking to perform visual servoing.

To identify and locate pallets in the working area of the autonomous forklifts, the detection system scales and applies homographic transforms to the 2D pattern. This method allows to obtain the pallet pose using 2D images with the forklift motionless, but with a high computational cost, even using low resolution images. To allow detecting and tracking a pallet, in the second mode we use a ROI (Region Of Interest) -to restrict computational needs- in full resolution, using the pattern scale and transform values obtained in the first mode. Using the detected position in the 2D image and applying geometrical transformations we obtain the pallet pose relative to the forklift. To improve robustness and reduce computational time further, the detection system makes use of the vehicle odometry to perform visual servoing on pallet handling.

The first camera is used to locate pallets on the floor and the second camera is used to locate pallets on shelves. In this latter case, only a scale transform is applied to disambiguate the distance to the pallet, as load and unload operations are always performed with a fixed orientation.

 
11:20am - 1:00pmSES 9.3: Human-centred manufacturing
Session Chair: Margherita Peruzzini
Aula O (first floor) 
 

19. The benefits of human-centred design in industrial practices: re-design of workstations in pipe industry

Margherita Peruzzini, Stefano Carassai, Marcello Pellicciari

University of Modena and Reggio Emilia, Italy

Sustainable Manufacturing (SM) traditionally focused on optimization of environmental and economic aspects, by neglecting the human performance. However, recent studies (Zink, 2005) demonstrated how industrial plant’s costs, productivity and process quality highly depend on the individual human performance (e.g., comfort perceived, physical and mental workload, simplicity of actions, personal satisfaction) and how much hazardous positions and uncomfortable tasks finally costs to the company. The present paper defines a human-centred virtual simulation environment to optimize both physical and cognitive ergonomics in workstation design and demonstrates its benefits on an industrial case study in pipe industry. The proposed environment aims at overcoming traditional approaches, where analysis are carried out at the shop-floor when the plant is already finished, by providing a virtual environment to easily test and verify different design solutions to optimize physical, cognitive and organizational ergonomics.


72. Investigation into the applicability of a passive upper-limb exoskeleton in automotive industry

Stefania Spada1, Lidia Ghibaudo1, Silvia Gilotta1, Laura Gastaldi2, Maria Pia Cavatorta2

1Fiat Chrysler Automobiles Italy SpA, Corso Agnelli 200, 10135 Torino Italy; 2Politecnico di Torino, Italy

The fourth industrial revolution faces the technological challenge of human-robot cooperation in manufacturing process. Aim of this study was to investigate the effectiveness and user’s acceptance of a passive exoskeleton for upper limbs. Three different tests, involving static and dynamic tasks, were performed by 29 automotive operators without and with the exoskeleton. Main aspects and results of the testing campaign are presented in the paper. Potential issues associated to the introduction of these auxiliary devices in the automotive industry are briefly addressed, together with the open questions on how to assess the biomechanical workload risk, especially in the design phase.


77. On immersive Virtual Environments for assessing human-driven assembly of large mechanical parts

George-Christopher Vosniakos1, Julie Deville2, Elias Matsas1

1National Technical University of Athens, Greece; 2Ecole National d’ Ingenieurs de St Etienne (ENISE), 58 rue Jean Parot, 42023 Saint-Etienne, France

Α mechanical product is often assembled by humans in one or more workstations by use of tools and fixtures and following a plan entailing human motions with and without load. When designing such assembly workstations and pertinent assembly procedures it is necessary to assess their suitability at best before actually building and implementing them. In this work immersive Virtual Reality is promoted as a suitable assessment platform. Unity 3D was used for developing a virtual scene and the corresponding scenario for assembling an aircraft wing, riveting being the main assembly operation. Kinect 2 was used as a tracking device and the Oculus DK2 as Head Mounted Display ensuring user immersion. Thus, it became possible to track the movements of a real human worker performing riveting tasks by holding a real tool, whilst all the rest, i.e. wing, fixtures and factory environment were virtual. So far, no haptic feedback was materialised. The human’s motions were recorded and preliminary assessment was demonstrated according to standard ergonomic protocols, i.e. RULA (Rapid Upper Limb Assessment), REBA (Rapid Entire Body Assessment). In addition, a questionnaire regarding subjective assessment of the assembly tasks and risk calculation based on Hand-Arm Vibration Calculator (HAV) were employed as a pilot on a ten-person sample. Initial results indicate the potential of the virtual environment constructed in assessing both assembly workstation design and assembly plan / procedure design in the case of large mechanical parts.


102. The comparison study of different operator support tools for assembly task in the era of global production

Liang Gong, Dan Li, Sandra Mattsson, Magnus Åkerman, Åsa Fasth Berglund

Chalmers University of Technology, Sweden

As part of a global production strategy, many manufacturing companies locate their assembly plants in different countries around the world. While outsourcing final assembly closer to key markets has competitive benefits, these companies face new challenges with communication and dissemination of information. Concerning shop-floor operators specifically, these challenges affect the initial training and continuing improvement work instructions in particular. Emerging information and communication technology (ICT) have created new opportunities for supporting operators cognitively. In this paper, an immersive virtual reality (IVR) training environment for LEGO gearbox assembly was developed and tested. IVR technologies offer new opportunities where operators can access training and work instructions in an immersive environment, which could potentially improve and influence the operator performance and emotion. Both objective performance and subjective emotion were measured and the impacts were analyzed. The results were compared with four different operator support approaches and it was seen that IVR technology has the potential of improving operator and that further studies on integration, information, communication design and development of measurement methods are needed before the industry can benefit from the full potential of IVR technology.


218. A multipath methodology to link ergonomics, safety and efficiency in factories

Maura Mengoni, Marco Matteucci, Damiano Raponi

Departmen of Industrial Engineering and Mathematical Science, Polytechnic Univesity of Marche, Ancona, Italy

Risk Management has become a taken-for-granted form of practice for numerous manufacturing companies and in most cases a strategic factor for their success on the global market. It concerns with health and safety at works. Literature overview proves that the control and management of risks allow companies to prevent accidents, improve the production efficiency and the employees’ psychosocial well-being. In this context, the assessment of ergonomics has been recognized to be a key factor to prevent most risk factors such as awkward postures, heat and contact stress, repetition, etc.

In the last years, numerous Virtual Prototyping-based tools have been developed to simulate human behaviors in virtual contexts and the adopted validation set-ups have proved to be effective for ergonomic purposes. However, most researches do not propose any structured methodology to investigate the strong correlation among the three elements affecting ergonomics (i.e. cognitive, physical and organizational), work efficiency and risk factors, all contributing to achieve health and safety in production especially when employees must carry out manual operations. The present work starts from the consideration that only if it is possible to link the above-mentioned aspects, the results of human behavior simulations can drive the research of solutions to manage potential risks. This correlation actually gives evidence of the impact of ergonomics on work efficiency and injuries’ reduction and as a consequence companies are more confident to adopt the proposed strategies.

The research goal is to define a multipath methodology that drives the analysts to find the proper ergonomics factors impacting on specific safety elements, how they relate to the workspace, the adopted tools, the overall production environment and to the workers’ job, how to quantitatively and qualitatively measure these factors and which VP tools and experimental set-ups could be used to conduct simulations.

A case study is used to illustrate the methodology. It is a top-level line of hood for kitchens, whose production cycle is characterized by four manual operations.

 
11:20am - 1:00pmSES 9.4: Sustainable Manufacturing
Session Chair: Yi-Chi Wang
Aula P (first floor) 
 

373. Simulating a Semiconductor Packaging Facility: Sustainable Strategies and Short-time Evidences

Yi-Chi Wang1, Tin-Chih Chen1, Li-Chih Wang2

1Feng Chia University, Taiwan; 2Department of Industrial Engineering and Enterprise Information, Tunghai University, Taichung, Taiwan

Semiconductor packaging plays a crucial role in semiconductor manufacturing because it is among the closest steps to the end customers. However, the complexity of production conditions makes controlling a semiconductor packaging facility a challenging task, and dynamic factory simulation has been considered as an effective means to fulfill this task. The large amounts of money, time, efforts, and expertise required to conduct a factory simulation study force a semiconductor packaging firm to pursue the persistent application of the factory simulation model (i.e., the sustainability of the factory simulation model). This challenge has rarely been discussed in previous studies. This study proposed several strategies to enhance the sustainability of a factory simulation model. In addition, the effectiveness of these strategies were examined by identifying short-time evidence rather than observing for a long duration to enhance efficiency. The proposed methodology was applied to the simulation of a real semiconductor packaging facility.


277. Optimization of energy efficiency of a production site: a tool for a fast data acquisition

Ivan Meo, Alessandra Papetti, Fabio Gregori, Michele Germani

Università Politecnica delle Marche, Italy

Nowadays the efficient use of energy has acquired a significant importance in different sectors, particularly in the industrial one. In the latter, many companies adopt policies aimed at sustainable manufacturing, reducing production costs to be more competitive on the market. Even the increasingly stringent regulations on environmental impact lead companies to tread a path towards energy efficiency in short terms to avoid penalties.

Hence the need for a tool that favors the audit of plant energy flows and the identification of existing criticalities in a fast and effective manner. This permits to evaluate the plant energy efficiency. Moreover, tools to monitor processes are increasing in terms of technologies. Digitalization of data is an opportunity to acquire real-time data for deep analysis and optimization. Data without a correct organization are useless for a correct plant management.

The goal of this work is to propose a structured data framework to perform fast and intuitive energy monitoring analysis. A method to effectively acquire plant data will be provided. The method starts from a classification of necessary data, such as the amount of energy or the number of hours worked, then propose an acquisition process that adapts to each energy carrier and to every production process. A resulting tool is proposed for a proper data collection. The tool collects data from different fields of the plant, arranging inputs for deeper energy analysis. The tool permits to identify in a clear manner plant limits in terms of energy use. An energy manager through the tool can propose fast solutions to overcome plant criticalities.

The tool is based on the data needed to characterize the flow of energy of various processes and services of the plant; a proper organization of data will be provided. The work will be validated exploiting the method than the proposed tool in a case study concerning a manufacturer of heat exchangers which decided to embark on a path toward energy efficiency without any supporting tool. A rapid and automatized implementation of the instrument will be the next step of the present research.


4. Smart Life Cycle Monitoring for Sustainable Maintenance and Production – an example for Selective Laser Melting machine

Eckart Uhlmann1,2, Rodrigo Pastl Pontes1, Abdelhakim Laghmouchi1, Claudio Geisert1, Eckhard Hohwieler1

1Fraunhofer Institute for Production Systems and Design Technology, Germany; 2nstitute for Machine Tools and Factory Management IWF - Technische Universität Berlin, Germany

Smart linking, evaluation and provision of information over the life cycle of a product are becoming growingly important. The use of information extracted from the combination of condition monitoring data, product data from the design and development phase, and from the product utilization phase, such as documented observations during the maintenance events will increase the availability of production machines and reduce the costs and resources caused by machine downtime. This knowledge and the correlations identified from the intelligent linking of the information over the life cycle of a machine can be provided to different stakeholders (e.g. service technician, maintenance planner, product developer, etc.) depending on their needs and requirements. This enables a sustainable maintenance, development and operation of the machines in the production environment. Moreover, the analysis of condition data and energy consumption of a production system and their linking with information from different phases of the life cycle of the machine, using intelligent approaches for data measurement for data acquisition, IT-infrastructure for data transmission, storage and provision, diagnostics and prognosis algorithms for fault detection and forecasting of the remaining useful life, will optimize the operation of the machine and increase availability and reduce costs for maintenance, repair and overhaul. The aim of this paper is to present a concept of a smart linking, evaluation and provision of the information over the life cycle of a production system to increase the performance and the efficiency for maintenance events.


370. The effect of forklift driver behavior on energy consumption and productivity

Abdulhameed Al-Shaebi1, Nourma Khader1, Husam Dauod1, Joseph Weiss2, Sang Won Yoon1

1State University of New York at Binghamton, United States of America; 2The Raymond Corporation, Greene, NY 13778, U.S.A.

This research investigates the impact of forklift driver behavior on energy consumption and productivity (i.e., the average number of pallet movements per operating hour) by conducting various statistical and regression analyses. Forklift driver behavior data are collected from actual warehouse setting to evaluate the relationships between different driving behaviors (i.e., concurrent travel and lift, travel speed, acceleration, and braking) and driver performance. The research results show that 1) drivers perform similar tasks have different driving behaviors; 2) driver productivity increases with longer durations of concurrent travel and lift; and 3) average speed is the most significant variable that affects the energy consumption.


122. Energy Usage Analysis of Carbide End Mills on AISI 1045 Steel

Oscar Velásquez Arriaza, Besmir Cuka, Jong-Young Lee, Dong-Won Kim

Chonbuk National University, Korea, Republic of (South Korea)

Machining and manufacturing processes have a strong influence on industry development and economy growth. Many important factors have been studied in order to reduce the waste in these processes, as well as to optimize them. The energy and power is a good parameter to verify the efficiency of the processes, and it can be used for process monitoring. Monitoring the state of energy being used may serve as an indicator on the manufacturing process behavior and efficiency. The main issue is to translate the energy usage into a practical indicator since the energy indicator is a sort of tough challenge to approach due to the dynamic characteristics of the machines and the diversity of associated factors interacting one another during the machining processes.

Another important issue that has a deep impact on both cost and efficiency, especially in computer assisted processes, is tool wear and tool life expectancy. Although it has been ceaselessly studied over many years, it is a complex task to solve still to these days. Thus, in this study a specific type of carbide end mill is analyzed through a potential energy approach over the conventional end milling. Energy limit for a cutting tool with specific physical and chemical features will be estimated since it can simplify the tool life estimation and the tool change timing prediction. A series of experiments are performed with carbide end mills against AISI 1045 steel, periodically measuring the tool wear and the required energy till the end of tool life.

 
11:20am - 1:00pmSES 9.5: Additive Manufacturing
Session Chair: Massimo Martorelli
Aula Q (first floor) 
 

308. Design for Automation: The Rapid Fixture Approach

Ruben Förstmann, Johannes Wagner, Kai Kreisköther, Achim Kampker, Dennis Busch

RWTH Aachen, Germany

As product varieties rise and lifecycles shorten, development approaches need to be adapted. Current trends aiming to solve the dissonance of reduced time to market and increased product variety include agile methods. In this context not only product design processes need to be adapted but also development of production processes and manufacturing equipment. At the example of fixture design, this paper presents an approach which allows an agile provision as well as a reconfiguration of equipment. The solution presented consists of a fixture design concept consisting of design rules which allow implementation into a tool for automated fixture design.


140. Print-in-Place of Interconnected Deformable and Rigid Parts of Articulated Systems

Francesco Rosa1, Monica Bordegoni1, Andrea Dentelli2, Alessandro Sanzone2, Andrea Sotgiu2

1Dipartimento di Meccanica – Politecnico di Milano, Milano I-20156, Italy; 2Graduated Student, Politecnico di Milano, Milano I-20156, Italy

In spite of the initial enthusiasms, as the experience in this field grows, it is becoming more and more evident that adopting an Additive Manufacturing (AM) process is advantageous only in those situations where its peculiarities can be fully exploited in order to realize “something” that cannot be realized otherwise and/or to shorten and/or simplify a production cycle.

In this perspective, this paper presents two case studies where two of the most “fascinating” and peculiar capabilities of the AM techniques are exploited to further improve two systems already manufactured with an AM (Fused Deposition Modelling - FDM) technique.

The Print in Place (PiP) and the Multi-Material Deposition (MMD) capabilities have been deployed to produce a stable junction between rigid (Poly-Lactic Acid, PLA) and flexible (Thermoplastic polyurethane, TPU) materials in order to realize hinges without any assembly operation. The development of such a junction is not trivial, since PLA and TPU do not adhere because of the chemical and/or thermal bonds that may generate during the FDM deposition process. Actually, their adhesion is usually unwanted because PLA is typically used to create the supporting structures of TPU objects. Therefore, a specific geometry has been created to guarantee a proper and durable junction.

More in detail, this solution has been used to develop two types of end effectors: an adaptive robotic grip, based on the fin-ray effect, and a flexible hand, based on the well-known and wide spread “flexi-hands”.

At a glance, each finger of the adaptive robotic grip is made of a triangular deformable structure, two edges of which are connected by means of rigid rods. Usually these rods are manufactured separately and then mounted on the triangular deformable structure. The developed junction allows for printing the rigid rods together with the deformable structure.

For what concerns the second case study, i.e. the flexible hands, two manufacturing solutions exist. The first and simpler method consists in manufacturing it as a single TPU flexible part. The second approach consists in printing several parts (phalanxes, palm and deformable junction elements), which have then to be assembled. The developed junction allows for creating and assembling all these parts in a single process.

As a conclusion, this paper presents two practical applications of an innovative solution for joining rigid and deformable materials, in order to develop articulated systems in a single operation.


245. Impact of Merging Components by Additive Manufacturing in Spare Parts Management

Milad Ashour Pour, Simone Zanoni

University of Brescia, Italy

Purpose – As manufacturers and researchers continuously look for more appealing approaches towards improved applications and better integration of machinery based on Additive Manufacturing (AM) technologies in different fields of industry, spare parts sector has been demonstrating more promising signs of progress for further implementation of AM. One of these signs lies within merging components of maintenance spare parts. From an operational point of view, with AM-in contrast to conventional methods of production-functionality comes before and above complexity of the design, and thus, manufacturing functionally enhanced parts characterized by the least possible number of assemblies whose design complexities can be matched with customers’ desired requirements becomes more feasible and accessible. From a strategic point of view, the just-in-time nature of AM-based productions eliminates the need for having large warehouses which are always accompanied with resource demanding inventory keeping practices.

The purpose of this paper is to investigate how consolidation of spare parts through reduction of their sub-assemblies can be influenced as an additive technology is used for production of various components that make up the final part composition.

Design/methodology/approach – The approach is based on parametric analysis of the main factors that influence the total incurred cost resulting from acquisition and management of the spare parts. These are the spares which are used to maintain and repair the parts that are used in the final product. A plausible classification of these factors is done to account for both the manufacturing method, and the product structure itself. While the primary set of factors include effects of production cost, reliability effects, and logistics cost to account for the manufacturing method, the secondary set of factors include cost and reliability distribution of the components to incorporate the product specific features in the study.

This process is performed by considering a base structure for the part composition and inclusion of final components which are produced with the current conventional methods (as-is), and then comparing this with an established list of all possible alternatives that include merger of components produced by an AM technology (to-be).

Findings – The sensitivity analysis in this study demonstrates the factors and their combinations that mainly affect the total incurred cost.

Value/Originality – This study provides an evaluation of all alternatives through an enumeration process. In the meantime, a further and in-depth investigation of maintenance and repair implications resulting from AM usage in spare parts industry is provided in order to identify the associated cons and pros.

Research limitations/implications – The main implication of this study is to understand how changing methods of production from a conventional process to an additive one for a multi-component product composition could alter the use-phase of components in medium to long terms. This can be a building block to perform a more comprehensive and extensive future research to include more sophisticated product structure and logistics for analysis of spare parts consolidation.


133. The Role of Additive Manufacturing in the Era of Industry 4.0

Mecid Ugur Dilberoglu, Bahar Gharehpapagh, Ulas Yaman, Melik Dolen

Middle East Technical University, Turkey

The fourth industrial revolution, namely Industry 4.0, is the recent movement on intelligent automation technology. It offers cyber and physical systems to cooperate profitably, aiming to build smart factories. Additive manufacturing (AM) is one of the vital issues in the Industry 4.0, in which physical and digital world will be integrated together. Due to the essentiality of customization in Industry 4.0, superior manufacturing methods over the conventional ones are needed to be developed. AM plays an important role in manufacturing customized/personalized products by its ability to create sophisticated objects with several materials. In this new era, utilization of 3D printing technology may turn any computer into a small factory.

Currently, the AM is being used in various industries, such as aerospace, biomedical, casting etc., along with an increase in the number of customized products. Although there are still some doubts about its applicability in mass production, availability of additive manufacturing in the industry rises with the new developments. Being a developing technology to create accurate and strengthened complex objects with increased manufacturing speed, AM may offer a way of replacing the old manufacturing techniques in the future.

In this paper, a comprehensive review on additive manufacturing technologies is investigated in relation with Industry 4.0. The main objective of this review paper is to classify the novel knowledge on AM technology for the researchers and highlight its potential and future trends.

This review mainly focuses on three important subjects about additive manufacturing: recent advances on material science, process development for AM, and enhancements on design computations. Researchers have shown an increasing interest in material studies due to its direct relation with the applicability of AM in the industry. To create the object with improved characteristics, various materials have been examined including smart materials and multi-material printing. Recently proposed AM processes, especially the ones developed for various environmental conditions, are also to be discussed in this paper. Additionally, studies regarding the development on computational tools of design are to be surveyed as another trending topic in the field. Several examples will be presented to understand the role of AM in Industry 4.0.


70. A New Method for Generating Image Projections in DLP-type 3D Printer Systems

Ulas Yaman, Melik Dolen, Mecid Ugur Dilberoglu, Bahar Gharehpapagh

Middle East Technical University, Turkey

This paper presents a novel method for generating image projections required for Digital Light Processing (DLP) type 3D printer systems where the entire cross-section of the printed object is directly formed via projecting the image onto a vat of photopolymers. The main difference of DLP printers from the printers utilizing stereolithography (SLA) technique is that it uses conventional type of projectors to reflect the sliced parts onto the window of the vat. In SLA systems, one or more laser heads are required to scan the whole slice and it takes much longer for SLA to fabricate the same object. Considering the details of the proposed method, the cross-sections (i.e. slices) of the solid model to be printed are obtained with the given tolerance parameters. The cross-sections, which are initially represented as bitmap images, are then processed along particular directions to characterize the given features efficiently. Once the tree structure associated with a cross-section is attained, the data for each- and every slice are compressed via a novel lossless compression technique titled DY16 which makes good use of relative data encoding. The coherence between the consecutive slices (or images) are taken into account in this proposed paradigm. Apart from this new method, the performances of the different compression algorithms (such as Huffman coding, Arithmetic coding, LZW, run length encoding, JPEG 2000) are also evaluated through two test cases (e.g. Stanford Bunny and Helical Gear) having completely different topologies. The paper shows that the DY16 technique, which is suitable for fast real-time hardware implementation, yields satisfactory performance in terms of data compaction achieved in the test cases considered. The presented method is realized on Python computing platform whose hardware implementation could be conveniently carried out on small form-factor computers armed with powerful multi-kernel microprocessors / microcontrollers. In this case, there would be no need to transfer each slice (image) to the 3D printer. The compact code would be enough to fabricate the corresponding 3D part right on the 3D printer.

 
11:20am - 1:00pmSES 9.6: 3D reverse engineering
Session Chair: Lapo Governi
Aula R (first floor) 
 

234. Optical touch probe for the inspection of mechanical components

Sandro Barone, Paolo Neri, Alessandro Paoli, Armando Viviano Razionale

University of Pisa, Italy

Reverse Engineering (RE) techniques are widely used in all branches of modern manufacturing industry. In the field of mechanical engineering and industrial manufacturing, RE refers to the creation of geometrical documentation data from existing physical parts. When original drawings are not available, it is often required to reconstruct CAD models from the existing parts by exploiting digitization techniques. These models can be used for numerical analyses in order to improve the product effectiveness. Moreover, geometry inspection may be needed by manufacturers to check the components fulfillment of the given tolerances and specifications.

In general, the shape of an existing physical model can be retrieved by using contact or non-contact measuring devices. Traditional point-by-point systems, as mechanical probes, or full-field optical scanners may be adopted to acquire target surfaces characterized by complex geometries. Coordinate Measuring Machines (CMMs) with contact probes provide measurements with high accuracies, but on-site measurements are not allowed due to the bulky equipment. Articulated arms, characterized by 6 or 7 DoF, can be alternatively used. These systems, equipped with either a laser line scanner or a touch probe, can be manually moved with respect to the target object, resulting particularly effective for on-site measurements. Anyway, both CMMs and articulated arms only provide a limited number of sampling points and are not suitable if free-form shapes must be reconstructed. Among non-contact approaches, optical methods based on the triangulation principle are able to provide full-field measurements with minimal interaction with the operator. Laser line scanning and structured light scanning can be used to obtain dense point cloud data on the measured surfaces. Optical techniques allow the acquisition of visible surfaces, whereas the digitization of internal geometries (i.e., slot, holes) is subjected to partial or complete restrictions due to optical occlusions. For this reason, complete reconstructions providing visible and internal geometries should be obtained by integrating contact and non-contact methodologies.

In this paper, an automatic and versatile 3D measurement system has been developed by integrating tactile and optical probing. In particular, a hand-held tactile probe and a stereo structured light scanner are combined to perform reliable multi-sensor measurements of mechanical components. The tactile probe is optically tracked by the stereo camera system of the optical scanner by means of 3D measurements of a prismatic flag, rigidly connected to the probe, and equipped with multiple chessboard patterns differentiated by QR codes. The probe configuration has been designed to provide both versatility and adaptability to various applicative contexts. Moreover, a suitable calibration process has been developed to relate the probe tip with respect to the tracking flag. The passive stereo cameras system is further augmented with a multimedia light projector in order to compose a structured light scanner. Full-field measurements of visible surfaces (i.e., external shape of the impellers) can then be integrated with point-by-point measurements of non-visible surfaces performed by the tactile probe, thus providing complete reconstructions of industrial components having complex shapes. The effectiveness of the developed multi-sensor system has been finally tested in the surface reconstruction of mechanical parts.


235. Digital Image Correlation based on projected pattern for high frequency vibration measurements

Sandro Barone, Paolo Neri, Alessandro Paoli, Armando Viviano Razionale

University of Pisa, Italy

The vibrational response of mechanical components is a crucial issue in several industrial fields. In particular, rotating machineries represent an application subjected to high vibrational solicitations, and generally, the bladed wheels are the critical part of the machine. The characterization of the critical components is generally performed through numerical simulations, but also experimental validation is essential for safety issues. Experimental Modal Analysis and experimental Harmonic Response Analysis are then valuable tools for machine validation. Several contact techniques were developed to measure the dynamic response of the components such as extensimeters or accelerometers. Anyway, those contact sensors may influence the response of the component and have severe limitations in data transmission when the component is rotating. For this reason, non-contact techniques were developed. The most commonly adopted sensor is the Laser Doppler Vibrometer (LDV), which guarantees high sensitivity measurements in a wide frequency range. Even if LDV is able to perform fast surface scans, it is limited in the measurement orientation. Moreover, it only provides velocity measurements along the laser beam direction, thus giving 1D information. The present work is aimed at developing a full-field optical method for the measurement of vibrating machinery components. The final target is a 3D acquisition system based on a couple of stereo cameras, capable to acquire vibrational response of components in the range 1-10 kHz. However, in this work, preliminary results have been obtained by using a single standard camera (having a resolution of 2 Mp), thus determining only a 2D displacement field through Digital Image Correlation (DIC) algorithm applied to a projected pattern. This approach has been followed in order to validate the feasibility of the proposed methodology, providing, at the same time, information about the camera specifications considering the measured vibrational frequency. Expensive high-speed cameras were discarded due to their cost and limited resolution. Low frame rate cameras were instead selected, having a short exposure time (20 μs). The available frame rate, however, would not allow to measure high-speed vibrations due to the Nyquist-Shannon theorem. Anyway, the excitation can be arbitrarily imparted by an electromagnetic shaker. For this reason, a single sinusoidal component at a given (known) frequency has been used, thus allowing the reconstruction of high frequency phenomena with low frame rate acquisitions by properly triggering the camera. The more severe limitation is then represented by the exposure time, which must be much lower than the vibration period (100 times was chosen in the present paper), so that the measurement target appears still during the acquisition of the single frame. Preliminary tests showed encouraging results, so that future developments were planned to achieve 3D measurements by adopting a stereo camera pair. In particular, the proposed system hardware exploits two cameras assembled in a stereo configuration and a multimedia projector used to project a speckle pattern. Digital Image Correlation (DIC) techniques could then be adopted to achieve 3D displacement measurements of the vibrating component.


262. Fast and low cost acquisition and reconstruction system for human hand-wrist-arm anatomy

Monica Carfagni1, Rocco Furferi1, Lapo Governi1, Michaela Servi1, Francesca Uccheddu1, Yary Volpe1, Kathleen Mcgreevy2

1Department of Industrial Engineering, Via di Santa Marta 3, Firenze 50139, Italy; 2Research, Innovation and International Relations Office, Meyer Children's Hospital, Viale Gaetano Pieraccini, 24, Firenze 50139, Italy

Dedicated 3D body scanners are paramount to deliver the exact measures of a human body to be used in a range of applications dealing with health, fashion and fitness as well as in several reverse engineering applications for robotics, automotive and computer vision in general. 3D human models obtained from 3D scanning foster personalized manufacturing in many applications, since they can be used to develop custom products perfectly tailored to the specific user.

Human oriented 3D scanners (the so-called body scanners) pose new challenges in the panorama of existing optical measurement systems; in fact the agile human nature, imposes the acquisition to be specifically fast to avoid movement artefacts. Nowadays very good results are possible with existing body scanners (both professionals and consumer devices); however, when focusing on relative complex shape of some body details (e.g. hand-wirst), obtainable results still lack completeness and accuracy.

In fact, human hand represents one of the most challenging parts to measure, yet it is required in a variety of applications.

Taking advantage from the emerging 3D depth cameras technologies, in this paper we present the design of a new, compact, low cost 3D dedicated hand-wirst-arm scanner system, able to deliver a full 3D point cloud in less than three seconds.

The system comprises 7 to 8 commercial devices, appropriately arranged on an adjustable structure made of two annular frames in order to allow the scanner to operate on body dimension rising from 4 years old to adult subjects.

The scanner is tested on a case study, represented by the design of custom orthosis. The semi-automatic reconstruction procedure, resulting in a parametric CAD model of the human wrist and thumb anatomy is also presented.


321. Enhancing porcelain whiteware quality assessment by means of Reverse Engineering-based procedures

Rocco Furferi1, Luca Ganugi2, Stefano Giurgola2, Lapo Governi1, Luca Puggelli1, Yary Volpe1

1Università di Firenze, Italy; 2Richard Ginori srl, viale Giulio Cesare 50, Sesto Fiorentino, 50019, Italy

During sintering process, porcelain changes its chemical composition as well as its physical and mechanical properties. In fact, the raw materials – which are a mixture of about 50% kaolin, 25% feldspar and 25% quartz – are initially processed and reduced to fine powder. Successively the primitive shape of the artefact (named "green body") can be obtained in several alternative forming process such as slip casting, isostatic pressing and plastic forming.

Once the initial shape is formed, the artefact undergoes at least two subsequent thermal processes: the first one, called bisque-firing, allows to improve the handling capabilities of the material in order to proceed with glazing (and decorating if required) limiting the risk of fractures. The last one is the final firing, during which the sintering is completed and the final characteristics of the artefact are reached.

The most relevant effect of the transformations induced by above mentioned process is a significant change of shape, which is a combination of shrinkage and pyroplastic deformations (i.e. deformations due to gravity, caused by softening).

Both of these deformations are taken into account during the definition of the green body shape. However, due to the complexity of the transformations and the high number of factors that can influence them, some variability is expected during the production process. Eventually, this leads to a significant scatter among the obtainable geometries of the manufactured pieces: deformations that occur during the manufacturing of a specific artefact may significantly vary even among the same batch.

For this reason high quality porcelain production requires a severe control on the produced articles and in particular on the production of tableware (dishes). More in deep, three parameters are monitored among the final pieces: the drop of the well, the bending of the rim and – whether the artefact is axial-symmetric - the circularity of the artefact.

These three parameters are evaluated by means of calibres and comparators on a number of samples at the end of the production cycle. However, these procedures are affected by typical drawbacks of hand-made measurements such as, for instance, limited repeatability and inaccurate evaluation. With the aim of enhance the quality measurement accuracy, in the present work an alternative approach – based on 3D laser scanning and reverse engineering based methods- is proposed. The virtually reconstructed shape of fine porcelain products, obtained by using a 3D scanner, is processed to extract, and possibly to re-think, the three quality parameters and to redefine them as reverse engineering standard procedures. The devised procedure mainly relies on the unlimited accessibility to the virtual geometry, taking advantages from computer aided measurement, and allows a more deep capability of investigating the product quality. Tested against a number of case studies, the proposed procedure proves to be effective in providing accurate, reliable and repeatable quality parameter measurements.


322. AUTOMATIC FEATURES RECOGNITION FOR ANTHROPOMETRY

Luca Di Angelo, Paolo Di Stefano, Caterina Pane

University of L'Aquila, Italy

The biological objects are morphologically-complex elements, which performs a particular physiological function. In many applications, geometric and dimensional parameters of these components of human body are analysed to gather some evidence, which may be useful in medicine, in anthropology and forensic investigations. In every of the previously described applications, measures are required to be accurate enough to discriminate the factor being investigated.

Generally speaking, the measurements are performed in-vitro or in-vivo. In the first case, manual measuring devices, such as sliding caliper and a goniometer are used. In-vivo, when the component of human body is available in the form of a 3D geometric model (as it is the case of CT-scans) its measurement is performed as point-to-point distance between points manually selected by the operator in a specific software. All these approaches are not structured since the measure is not associated to an ideal feature as prescribed by GPS standards. It is mainly for this reason that this kind of measures are affected by wide uncertainties.

At the purpose to reduce the measurement uncertainties, the authors presented a new automatic method to measure morphologically-complex objects, which takes advantage from the representation of the object in the form of 3D geometric model obtained from CT-scans or 3D scanning. In this work the method is verified in real cases and compared with the traditional approaches.

 
1:00pm - 1:50pmLunch break
Courtyard at ground floor 
1:50pm - 2:20pmPOSTER: Poster Session
TBD
Gallery at first floor 
 

109. Architecture and Implementation of an Interface for Intelligent Tools in Machine Tools

Hendrik Vieler, Armin Lechler, Oliver Riedel

University of Stuttgart, Germany

Nowadays a growing number of additional features, provided by intelligent tools, are used in machine tools to improve the quality of machined products or to enhance functionality of machine tools. This brings some problems concerning interfaces as each manufacturer of additional tools uses his own interfaces, which may exclude others. Additionally, developing a new intelligent tool always includes development of solutions to transfer energy and data from the static environment into the turning tool. This is a big obstacle especially for small and medium enterprises. Having manufacturer dependent interfaces the users of intelligent tools must put a high effort into integration. Every time a new manufacturer’s tool is to be used, this integration has to be done again.

A new standardized interface for intelligent tools tries to solve this problem. It includes electrical contacts at the HSK flange contact surface for the transmission of energy and data and a device to transmit energy and data contactless from the static environment of the spindle to the rotor of the spindle. Furthermore it includes an electronic component which integrates the additional tool into the Ethernet based bus of the machine. The communication can be configured by the user of the interface in two ways: An easy way giving little, but nevertheless for most applications sufficient, capabilities. Second a solution, which gives almost full control to the user, but is significantly more complex to use.

Viewing the intelligent tool alone or together with its interface to the bus as a Cyber Physical System (CPS) makes it possible to gain further use of the tools. Its data can be used for several more sophisticated tasks including condition monitoring, optimization of processes or big data scenarios.

In this paper the concept of the interface is presented, together with the overall system architecture which was developed. The transfer to practical use will presented by an actual implementation.


134. Novel method for selection of drive motor in paperboard forming press utilizing multi-dynamics model

Sami Matthews, Panu Tanninen, Amir Esmael Toghyani, Harri Eskelinen, Sami-Seppo Ovaska, Juha Varis, Ville Leminen

Lappeenranta University of Technology, Finland

Due to environmental factors, paperboard as a natural cellulosic fibre material is being used increasingly as a packaging material. Applying an understanding of the material thickness properties of paperboard to a multi-body dynamics analysis makes it is possible to simplify the machine construction and prototype phase of a machine design of a paperboard forming press. The method involves integrating an empirical multi-dynamics simulation model using commercially available software to save time in mechanical design. This work concentrates on effect of thickness in pressing force of 4 different SBS-coated paperboards. Experimental force is measured utilizing linear servo driven press and the derived data is plotted into into Matlab as polynomial curve function and utilized in multi-dynamics program Adams by Simulink-interface. The semi-empirical practical method with light computation time presented in this paper can be utilized for various fibre materials and pressing techniques to streamline the design phase.


137. Data and Information Handling in Assembly Information Systems – A Current State Analysis

Pierre Eric Christian Johansson1,2, Martin O. Enofe1, Moritz Schwarzkopf1, Lennart Malmsköld3, Åsa Fast-Berglund2, Lena Moestam1

1Volvo Group Trucks Operations, Sweden; 2Chalmers University of Technology, Gothenburg 412 96, Sweden; 3University West, Trollhättan 461 86, Sweden

Products become more complex as the general technology development reaches new levels. These new technologies enable manufacturing companies to offer better products with new functionalities to their customers. Complex products require adequate manufacturing systems to cope with changing product requirements. In general, manufacturing of this type of products entails complex structured and rigid IT systems. Due to the system’s complexity and comprehensive structure, it becomes challenging to optimize the information flow. There are improvement potentials in how such systems could be better structured to meet the demands in complex manufacturing situations. This is particularly true for the vehicle manufacturing industry where growth in many cases has occurred through acquisitions, resulting in increased levels of legacy IT systems. Additionally, this industry is characterized by high levels of product variety which contributes to the complexity of the manufacturing processes. In manual assembly of these products, operations are dependent on high quality assembly work instructions to cope with the complex assembly situations. This paper presents a current state analysis of data and information handling in assembly information systems at multiple production sites at a case company manufacturing heavy vehicles. On basis of a certain set of characterizing manual assembly tasks for truck, engine and transmission assembly, this work focuses on identifying what data that is used in manufacturing engineering processes and IT systems to produce assembly work instructions. This work aims to identify gaps in the information flow between manufacturing engineering and shop floor operations.


145. Effects of mould surface roughness on press forming process of polymer coated paperboard

Panu Tanninen, Sami Matthews, Ville Leminen, Antti Pesonen, Harri Eskelinen, Juha Varis

Lappeenranta University of Technology, Finland

In paperboard press forming the forming forces are transmitted on the formed substrate by controlling the sliding of the blank with a blank holding force. A set value of the force and the friction between the tool surfaces and processed material define the force transferred on the formed substrate. Mould surface roughness is one of the main factors affecting the magnitude of friction. A series of surface roughness measurements was made to investigate the surface roughness in different areas of two different blank holders to determine a sufficient quality for the tool surfaces. Also the static friction coefficients of formed substrates were determined and the friction force distribution was investigated. The results show that the effect of mould temperature on friction force can be reduced significantly by mould surface polishing, making the press-forming process easier to adjust. Hence, the polishing of mould surfaces can be recommended.


16. A theoretical background for the reconfigurable layout problem

Isabela Maganha, Cristóvão Silva

University of Coimbra, Portugal

The traditional layout problem has been studied for decades. It concerns the machine’s placement to appropriate locations, considering a single planning period in order to minimize material handling costs.

The current market context is characterized by global competition between industries, high product variety and variable volumes. Those are key factors that requires the launch of products with a short life cycle and a high customization degree. In this context, the layout configuration must be able to meet the needs of a dynamic and uncertain environment, being more flexible, modular and easily reconfigurable. Furthermore, besides considering only material handling costs when designing a layout, as in traditional approaches, increasing customers’ responsiveness through shorter lead times and lower work in process levels must also be taken into account.

The main strategies proposed to cope with flexibility issues in layout design are: (1) dynamic layouts, (2) robust layouts and (3) reconfigurable layouts. The dynamic and the robust layout problem consider multiple future periods when considering the layout design, assuming that production data are available for future planning periods. But, in manufacturing systems, changes in production requirements usually are unexpected or only known slightly ahead of the next production cycle. Thus, the reconfigurable layout problem (RLP) seems to be the most adequate option for real manufacturing problems since it considers only production data concerning the next planning period.

RLP can be defined as “the ability of a layout to rearrange rapidly and frequently, with minimal effort, to adjust its configuration to new circumstances, considering system operational performance and providing the exact capacity and functionality needed, when needed”. Therefore, the RLP aligns for the notion of real-time enterprise, because the changes in the layout configuration should occur rapidly and be readily available, while the production system keeps operating on the edge by doing real-time layout adjustment with live data.

The main objective of this paper is to propose a theoretical background for the RLP by conducting a systematic literature review (SLR) about the subject, which is a formal approach that adopts a replicable, scientific and transparent process to locate, select, analyses, synthesize and report evidence.

In this paper, the process followed to conduct the SLR about the RLP is described, in which 60 papers were identified. A qualitative and quantitative analysis of those papers are also conducted and described. The results are presented and discussed, contributing to a better understanding of the RLP and its implication for manufacturing systems. Furthermore, research gaps and trends are identified and future research directions are pointed out.


169. Processing of real-time Data in Big Manufacturing Systems

Manfred Benesch, Hellmuth Kubin, Klaus Kabitzsch

Technische Universität Dresden, Germany

Today’s factories consists of many - too different - equipments, each with its own automation system - how SPS, PLC, MES, ... - and its own possible different and divergent real time clocks. Most of them work event based and the working cycle depends on events and will be different on different situations.

If that systems measure and store data there will be a lot of data not fitting really together using there timestamps. Let assume that the equipments sensors measure some values with a clock pulse every 10 seconds, sometimes maybe 9 or 11 seconds (jitter) and not at the same point of time over all equipments (clock drift).

After all we have data measured at the same point of time but with different stored timestamps because of the different clocks. If we look further to trends like industry 4.0 this behavior would be even more worse. For the industry 4.0 data from different manufacturer should come together, so there are even more differences in time based data.

One possible solution is storing data not time based but store it “OPERAND” based. This means that the measured data of the processes should be aggregated and stored with relation to the product that has been processed. With this type of data relation it's easy to combine data over manufactures. But in real world there are unfortunately many systems that only store data time based. Even if we want to aggregate this time based data and put it to the processed operands we have to handle the time based one.

Also to do dynamical or time series analysis we have to use time based measurements, so there is no way to get out of the problems of handling such data. Evaluation of data from only one equipment should not be problematic, because there should be only one clock. But if there are different sampling rates and the normal jitter, its not that easy any more. Think about an equipment with same processing and measurement chambers. Moving the operand from processing to measurement takes some time so the corresponding processing data for the measurement is shifted in time. For correct use of such data the correct ones have to put together. Moving the data against each other is the way to go, but if the data is not equidistant (jitter, …) many values would not fit together after that time correction. Our developed solution for that is called a “fuzzy join” that fit data together, that have nearly the same timestamp. That “nearly” depends e.g. on the sampling rates of the signals. So its important to know a correct rate even on data with gaps – which are ignored for calculation - over long time period.

In ADM - a process analysing tool – all of this and many further problems are handled transparent for the user. Of course better/non faulty data quality (no jitter, only equidistant rates, …) would avoid such problems, but that’s not the normal case in real world.


66. Modelling Capabilities for Functional Configuration of Part Feeding Equipment

Michael N. Hansson1, Eeva Maria Järvenpää2, Niko Siltala2, Ole Madsen1

1Tampere University of Technology, Finland; 2Department of Mechanical Engineering and Industrial Systems, Tampere University of Technology, 33720 Tampere, Finland

This paper introduces a configuration framework for automatic configuration of production systems. The proposed framework consists of three key aspects; 1) functional configuration, 2) interface configuration and 3) behavioral configuration, that together offers the ability to automatically identify production resources, and aggregate them to form a production system. The main focus of this work is to model functional capabilities to facilitate automatic suggestion of part feeding resources, and exemplifies different approaches to model part feeding capabilities.


59. Improving Production Changeovers and the Optimisation: A Simulation-based Virtual Process Approach and its Application Perspectives

Khalid Mustafa, Kai Cheng

Brunel University, United Kingdom

Manufacturers have to compete in the global marketplace responsively in a continuous sustainable manner. To be responsive to the customers’ dynamic needs and lower the production cost, manufacturers often have to produce a verity of products on single production system along with agility and sustainability. It takes time and resources when a production system switching from one product to another particularly in a frequent time-stringent mode.

In this paper, a simulation-based approach is proposed by taking a holistic view of overall production changeover cycles while addressing the sustainability in the production process. The need of overall industrial sustainability in a production system is increasingly paramount due to several established and emerging factors. To improve the capability of the production system one of the important factors is reducing and managing production changeover time better. The simulations are the enabling technology for virtual process mapping, undertaking quantitative analysis and the process optimization. An industrial case study is carried out on a food production plant. The production performance can be improved by identifying and eliminating non-value-added activities through process mapping and complexity reduction. To achieve maximum production and waste reduction, virtual production plant model is developed using Arena software by comparing existing production setup. The virtual simulation-based case study includes the changes in facility lay out, process automation, process mapping, manufacturing complexity issues, changeover cycles and sustainability in the production system.


384. Particle Size Distribution Estimation Of A Mixture Of Regular And Irregular Sized Particles Using Acoustic Emissions

Ejay Nsugbe, Andrew Starr, Ian Jennions, Cristobal Ruiz Carcel

Cranfield University, United Kingdom

This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated.


371. A novel methodology to integrate Manufacturing Execution Systems with the lean manufacturing approach

Gianluca D'Antonio, Joel Sauza Bedolla, Paolo Chiabert

Politecnico di Torino, Italy

In order to deal with global competition, industries have undertaken many efforts directed to improve manufacturing efficiency. From a broad perspective, two possible approaches are the adoption of lean manufacturing methodologies or the implementation of information tools: for several years, these two approaches have been assumed to be mutually exclusive. The present work aims to define a methodology to integrate Manufacturing Execution Systems with the lean manufacturing approach. A case-study in the field of aeronautics is presented to validate the method.


352. Physical Rigging for Physical Models and Posable Joint Designs Based on Additive Manufacturing Technology

Yingtian Li, Yonghua Chen

The University of Hong Kong, Hong Kong S.A.R. (China)

In 3D computer animation, there is a lot of ongoing research in rigging mesh or solid models so that the models can be easily converted to articulated characters that can generate vivid motion. Even though these articulated characters (can be an animal or a human character) can exhibit desired motion in computer, yet the joints that facilitate the motion are not actually designed at all. Instead, the joints are modeled as a set of equations defining the nature and range of the motion. In many cases, it is desirable to produce physical models of the animated characters for a variety of purposes such as pose evaluation by a team of engineers from different background. When a physical model of the animated character needs to be fabricated, all rigged joints must be clearly designed with consideration of mobility and manufacturability. In this paper, a physical rigging methodology is proposed. A simple joint design for physical rigging of articulated characters is also proposed. The proposed joint design can be easily used for both revolute and omnidirectional motion. Using the proposed joint design, it allows a physical character to assume any poses that are within the designed motion range after fabricated by additive manufacturing (AM) technologies. A number of sample designs have been fabricated using two popular AM technologies to demonstrate the effectiveness of the proposed method.


298. Machining accuracy improvement by compensation of machine and workpiece deformation

Mateusz Wąsik, Arkadiusz Kolka

SIlesian University of Technology, Poland

Current state of art in field of CNC machining systems is impressive. Advanced CNC machine tools themselves are really complicated mechatronic devices with a lot of possibilities and options, which give a potential to improve the accuracy and efficiency of production systems but it also means that the users’ knowledge must be at an appropriate level. Some compensation systems operate in the background to enhance the stability of machining and reduce the risk of errors form thermal conditions and geometrical errors influence. Mechatronic drive systems are flexible and able to adopt reducing the dynamic errors as a machining task. A lot of configuration options and a wide range of intelligent technologies are very useful and helpful but wrong driving adjustments may disturb production with wrong manufactured parts.

During the work at the implementation of flexible machining system for autonomous production some challenging difficulties were found. First of them is the problem with high accuracy machining of workpieces of thin wall and complicated shape. Applying high technology machine tools and specially prepared procedures cause that most of machining errors are minimized e.g. geometrical or drive position errors. Even thermal deformations of machines are effectively compensated. For workpieces of a regular shape, the achieved machining accuracy is satisfactory but for workpieces of a complex shape and thin walls form light alloys machining (e.g helicopters’ gearbox cases) it is still difficult to find proper environmental conditions without separating the machine form from among others outer temperature impact. While considering flexible machining systems, it is impossible to cover it completely or to stabilize the temperature in the production hall effectively. When the temperature outside and inside the machine tool is changing, it is necessary to compensate the influence of that by positioning systems adjustments or application of geometric active compensation units. Proposal of the procedure for adjustment and self-testing is prepared and verified successfully on the existing new flexible machining systems. Another problem is that if the temperature inside the machine is changing, the workpiece’s temperature is changing too and the shape is distorted, so that the machining accuracy is decreasing even if machine tool’s active systems compensate the machine’s thermal deformations.

An approach to improve the machining accuracy with high accuracy machining systems by using special adjustment procedures and additional workpiece’s distortion compensations are presented in the paper.


265. Efficiency & sustainability model to design and manage two-stage logistic networks

Marco Bortolini1, Francesco Gabriele Galizia2, Cristina Mora1

1Department of Industrial Engineering, Alma Mater Studiorum – University of Bologna, Viale del Risorgimento 2, 40136, Bologna, Italy; 2University of Padova, Italy

The distribution and storage efficiency together with the environmental sustainability are mandatory targets to consider when designing and managing modern supply chain (SC) networks. The current literature continuously looks for quantitative multi-perspective strategies and models, including and best balancing such issues that often diverge.

This paper presents and applies a bi-objective optimization model to best design and manage two-stage logistic networks looking for the best trade-off between the SC stock level and the building and distribution environmental impact. The existence of good balance confirms the possibility to reduce the average SC stock level without a relevant increase of the emissions due to frequent replenishments.


240. Skull Repair Using Active Contour Models

YuCheng Lin, Chen-Yang Cheng, Yi-Wen Cheng, Cheng-Ting Shih

National Taipei University of Technology, Taiwan

Skull defects will result in high risk of brain infection and low brain protection. In order to avoid risks and re-injury, we need to reconstruct the defect by grafting bone onto the deficient region. With rapid customization manufacturing of additive manufacturing (AM) and 3D printing (3DP) technology, the fitted shape of a skull prosthesis can be fabricated accurately and efficiently during cranioplasty surgery. However, an unfitted skull prosthesis made of artificial polymer or a metal implant can cause repeated infection, which may need an additional surgery. This paper presents a method to create suitable geometric graphics of skull defects to be applied in skull repair by using active contour models. The active contour models can be adjusted in every tomography slice, and the curves that represent the defect in the skull bone can be modeled. The generated graphics can adequately mimic and compensate for a fitted curvature. Clinical surgeons will be able to define, process, and implant a customized prosthesis to patients very quickly in surgery with this research. Especially, patients who have urgently skull defect problem can be solved and obtained maximum surgical quality.


238. Considering the performance bonus balance in the Vehicle Routing Problem with Soft Time Windows

WanChen Chiang, Chen Yang Cheng

National Taipei University of Technology, Taiwan

In the field of operations research, the Vehicle Routing Problem with Time Windows (VRPTW) has been widely studied because it is extensively used in practical applications. Some situations in the practice are discussed in the most of past relevant research, i.e., time window and vehicle capability. However, the performance bonus is not considered. In most logistics companies, performance bonus is calculated by the piece. But it is a problem that the method of calculation is not fair for all staff. In this paper, the model not only considers the performance bonus into the VRPTW, but also changes the calculation method to make a load balance between every staff. In the same time, it also makes the calculation of performance bonus more fair for all staff.


231. Dynamic coordination within a Lean Enterprise

Uwe Dombrowski, Philipp Krenkel, Thomas Richter

TU Braunschweig, Institute for Advanced Industrial Management, Germany

Many manufacturing enterprises act in a dynamic and partially unpredictable market. This is shown through shorter product life cycles, reduced forecast accuracy within the supply chain and frequently new product launches. In fact, there are strong fluctuations in the overall production volume and job profile. Rigid enterprises encounter on significant problems, if they are not able to coordinate targets precisely and quickly to all processes of a value stream. These circumstances lead manufacturing enterprises to transfer principles of Lean Production Systems to other business units such as development and service. Therefore, the goal is the development of a Lean Enterprise, which enables the overall consideration of all processes through the entire value stream. Through this comprehensive process orientation all actors can be linked together along the entire value chain. Therefore, internal and external stakeholders have to be considered. This can be seen as one basic factor for an overall coordination. Approaches that enable a dynamic coordination of all processes within a Lean Enterprise have not been derived yet. Considering this topic, this paper derives and describes an approach to determine objectives of the corporate enterprise strategy to the processes of all units through the entire value stream. In addition to this, processes can be quickly adapted to deal with dynamic and unpredictable markets. Thereby a dynamic coordination of all processes within a Lean Enterprise can be realized.


230. Development of Hybrid Quality Management System for Construction Equipment Part Industry

Hong Jin Jeong1,2, Bo Hyun Kim1, So Young Jung1

1IT Converged Process Group, Korea Institute of Industrial Technology, 143, Hanggaul-ro, Sangnok-gu, Ansan-si, 15588, Republic of Korea; 2Dept. of Industrial Management Engineering, Hanyang UNIV., 55, Hanyangdaehak-ro, Sangnok-gu, Ansan-si, 15588, Republic of Korea

Construction machine consisting of about 30,000 components has a complicated value chain and small quantity production compared to a variety of its types. The quality and durability are especially considered importantly in construction machine due to its long-term operation in extreme environments such as construction, mining and plant industry. The quality of construction machine highly depends on the quality of its parts; therefore, the quality process in parts manufacturers should be systematically managed. By combining the advantages of a packaged system that increases the recyclability of a system while decreasing the time required for system building, with the advantages of a customized system that improves the suitability of enterprise’s work process, this study is to development the hybrid quality management system (HQMS) containing the advantages of the two systems. Thus, the leading manufacturers of key parts in construction machine were selected to draw their functional requirements of system through the 4 step development process of requirements. Especially, the key performance indicator (KPI) and management performance indicator that are being actually managed by parts manufacturers are used in specifying and validating the functional requirements, and improving the objectivity of development process for requirements. In system design, the common functional requirements that are used in all companies are platform in a package and combined with the optional functional requirements preferred by individual company to build the customized system. In addition, the HQMS is operated in-house or by cloud service based upon the security policy established in each individual company, as well as provides users with customizing its main screen. This study implements the prototype HQMS as proposed in study and applies it to two parts manufacturers to show the positive effects of system design.


194. Supporting maintenance scheduling: a case study

Patricia Senra, Isabel Lopes, José A. Oliveira

University of Minho, Portugal

The scheduling of activities aims to establish “when” and “who” each planned task will be processed. Maintenance scheduling is concerned with the allocation of (scarce) resources to maintenance activities with the objective to optimize one or more performance measures. Considering the preventive maintenance, each (preventive) maintenance activity (referred as a "task") to be scheduled usually involves technicians, equipment, and spare parts. As a result of scheduling the sequence over time of all preventive maintenance activities is obtained with the resources assignment, that are converted into a set of daily service orders for the maintenance technicians.

The work presented in this article is part of a project aimed at improving the computerized maintenance management system (CMMS) of an automotive company. In the company, the preventive maintenance scheduling is "manually performed" by the planner supported by the CMMS that roles only as an information system. Therefore, nowadays the maintenance scheduling is a time-consuming task due to the high number of planned activities to be considered and all the constraints related with: the technicians' availability and their skills; the spare parts stock; and, mainly, the downtime of production lines that defines the equipment availability. And, as a consequence, the scheduling currently method evidences lack of effectiveness. This article outlines the development of an automatic and intelligent scheduling support tool. With this new tool, the scheduler can get a quick scheduling solution based on a proper objective function, through a methodology adequately studied and specified for this case study.

This paper considers a scheduling problem where each of n tasks has to be processed by m technicians, that is modeled as a scheduling parallel machines problem. For each maintenance activity there are a set of inputs, such as: deadlines, due dates, processing times, required competence level, technicians’ availability and equipment availability (task availability). In this initial approach, the objective function defined is the minimization of maximum weighted lateness (wLmax) to accomplish the maintenance activities. Different heuristics algorithms that can be applied will be also discussed, aiming the development of an adequate heuristic able to find good scheduling solutions, taking into account all the constraints and the objective function. The use of proper algorithms makes scheduling faster to deal with contingencies, reducing maintenance costs in a manufacturing process, enabling the company to increase its productivity. Computational experiments with several instances considering different objective functions are presented and the results are discussed.

The future works will focus on the development on a methodology considering specified additional constraints and enhanced objective functions and more suitable to this large real-world problem.


99. Modeling and Simulation of the Motorcycle’s Lowside Fall

Andrea Bonci, Riccardo De Amicis, Sauro Longhi, Emanuele Lorenzoni

Università Politecnica delle Marche, Italy

The deployment of active safety systems enhancing the motorcycle stability and supporting riders in defusing critical and dangerous driving situations is a topic of major concern in the two-wheel research community. In the design and development of safety control systems, setting up an adequate model of the controlled system is a key issue since it should be able to describe adequately the motion of the vehicle in critical situations such as precarious adherence, cornering brake and acceleration, or dangerous falls. In literature, these situations are typically investigated by means of black box approaches, namely by using multibody numerical simulators in which the equations governing the vehicle dynamics are unknown. In this paper, instead, the authors propose an analytical model as alternative to black box approach for the simulation of critical and complex motorcycle’s dynamics leading to falls. The model has been presented in author’s earlier works, it has a minimum degree of complexity, considers the rear wheel traction/braking and takes into account the interactions of longitudinal and lateral friction forces acting on the tyres. This analytical model has allowed to investigate the lowside phenomenon and the simulation results has been presented.


104. The Product Design Information Imaging at the Construction Stage in 3D-model Creation Tree

Denis Tsygankov1,2, Alexander Pokhilko2

1Ulyanovsk Mechanical Plant, 94 Moscow highway, Ulyanovsk 432022, Russian Federation; 2Ulyanovsk State Technical University, 32 North Venets st., 432027 Ulyanovsk, Russian Federation

This article is devoted to the designed product 3D-model information content imaging. As a rule, it based on the used CAD-systems abstract basic operations, not maintaining the mortgaged constructive meaning. Authors propose an approach for 3D-models information content presentation within the designed product subject area. This approach consists in basic operations generalization to the level of semantic macro functions. Such macrofunction different by fixed physical meaning, a specific set of design parameters and strict conduct. Such an approach will not only unequivocally correct to image information about the product design, but also facilitate the reuse of design decisions and their fragments.


125. Improving Supply Chain visibility with artificial neural networks

Nathalie Silva, Luis Ferreira, Cristovao Silva, Vanessa Magalhães, Pedro Mariano Neto

University of Coimbra, Portugal

The vulnerability of supply chains has been increasing in the last years. To increase competitiveness, many companies are more and more focused on lessening the impact of disruptions. The capacity to anticipate disruptions will allow companies to reduce risks, which increases higher levels of competitiveness.

To properly respond to disruptions, visibility across the supply chain (SC) is required. Supply chain visibility is the capability of sharing on-time and accurate data on customer demand, amount and location of inventory, cost of transportation, and other logistics dimensions throughout the SC. Therefore, SC visibility should include the capability for forward-looking, predictive views of the supply. By enabling visibility, many situations that could lead to disruptions in the SC can be identified and defused long before they reach a critical state. However, most authors either focus on simplified SCs (i.e. dyad, two-level supply chain, linear supply chain), which are far from the complexity of real environments.

This paper addresses these challenges by relying on an intelligent system (IS) to predict future status from historical data. A multi-echelon SC was developed in a simulator to generate data that could feed the IS. That data was used to teach the IS and give it the ability to recognize and extrapolate to future events based on new and untrained data.

In this paper, by applying artificial neural networks (ANNs), we intend to predict (1) the capacity to fulfil upcoming orders and their time in system and (2) which SC nodes will reach the re-order point and thus, require new orders upstream. That information will give the managers time to act, anticipate and cope with disruptions. Predictions were performed for different time horizons.

The proposed ANN approach allows to predict the capacity of the simulated SC to fulfil incoming orders for the next upcoming period with a recognition rate larger than 99%. This prediction for 10 upcoming periods presents a recognition rate of approximately 90%. Furthermore, the proposed approach allows, with a recognition rate of 97%, to anticipate which SC nodes will receive an order for the next upcoming period. These results are the base for a discussion on the use of ANN’s to increase SC visibility, thus allowing the planner to anticipate actions to avoid SC disruptions.


202. Investigation of the effect of grinding parameters on surface quality in grinding of TC4 titanium alloy

Zhao Tao1,2, Shi Yaoyao1, Sampsa Vili Antero Laakso1, Zhou Jinming2

1Aalto University, Sweden; 2Northwestern Polytechnical University, 127 West Youyi Road, Xi’an 710072, China

TC4 titanium alloy is widely used in the components of aero-engines, for example blisks and blades. As the key components of aero-engine, the surface integrity has significant influence on aerodynamics performance and service life. In order to improve the surface quality of TC4 titanium alloy parts, the effect of grinding parameters on surface integrity must be known. In this research, an experimental analysis has been conducted to understand the effect of main grinding parameters, including wheel rotational speed, feed rate, grinding depth and abrasive size, on surface integrity in terms of surface roughness and residual stress, and removal rate. In order to investigate the cross influence from different process parameters, a large number of workpieces and experiments are often required. Therefore, the workpiece used in this study are used instead of actual blade. Before conducting the experiment, test samples were pre-cut using same cutting parameters as processing blade. Three level single parameter experiments were design for each grinding parameter and the material removal rate and surface integrity regarding surface roughness and residual stress were measured after each experiment. The results of this study reveal that the surface parameters are affected significantly by the grinding parameters. While each grinding parameter has different level influence on surface parameters. Additionally, the results provide a reliable and useful data for improving the surface quality and processing efficiency of grinding the components of aero-engine.


293. Reliability assessment of a packaging automatic machine by accelerated life testing approach

Alberto Regattieri2, Francesco Piana2, Mauro Gamberi2, Francesco Gabriele Galizia1, Andrea Casto2

1University of Padova, Italy; 2Department of Industrial Engineering, University of Bologna, v.le Risorgimento 2, Bologna, 40136, Italy

Industrial competitiveness in the innovation, the time of the market introduction of new machine and the level of reliability requested implies that the strategies for the development of products must be more and more efficient. In particular, researchers and practitioners are looking for methods to evaluate the reliability, as cheaper as possible, knowing that systems are more and more reliable.

This paper presents a reliability assessment procedure applied to a mechanical component of an automatic machine for packaging using the accelerated test approach. The general log-linear (GLL) model is combined based on a relationship between several stresses, in particular mechanical and time based. The complete Accelerated Life Testing – ALT approach is presented by using Weibull distribution and Maximum Likelihood verifying method. A test plan is proposed to estimate the unknown parameters of accelerated life models.

Using the proposed ALT model the reliability function of the component is evaluated and then compared with data from field provided by customers regarding 10 years of real work on a fleet of automatic packaging machines.

The results confirm that the assessment method through ALT is effective for lifetime prediction with shorter test times.


305. Requirements for Education and Qualification of People in Industry 4.0

Andrea Benešová, Jiri Tupa

Faculty of Electrical Engineering at the University of West Bohemia in Pilsen, Czech Republic

Industry 4.0 is a new industrial revolution that was caused by the rapid development of new technologies such as automation, robotics and digitization. Development of new technologies not only fundamentally affect the industry and economy, but also has an impact on society-wide change. This change has an impact on security, labour market, social system and education. New technological changes will lead to the extinction of certain professions or industries and in turn contribute to the emergence of new professions. 4.0 The introduction of industry into enterprises leading to new principles of organization of labour organisation. Using these new technologies should be removed physically demanding work and improving the working environment, but will also increase the demands for flexibility and qualification of employees. The structure and workload majority of jobs in the companies will change and for this reason will be required from employee’s entirely new skills. The aim of this paper is to present an impact of Industry 4.0 concept into the organizational structures of industry companies. The paper tries to present changes in the organizational structure, thus new position, roles and results of analysis focused on definition requirement skills and qualifications for particular jobs.


324. The level of innovation in SMEs, the determinants of innovation and their contribution to development of value chains

Joanna Oleśków Szłapka1, Agnieszka Stachowiak2, Aglaya Batz2, Marek Fertsch1

1Poznań University of Technology, Poland; 2Brandenburg University of Technology Cottbus- Seftenberg, Universitätsplatz 1, 01968 Senftenberg, Germany

The article describes is a synthetic presentation of the innovativeness idea. It includes analysis of innovativeness level represented by companies of various sizes and industries from all over the world. The analysis leads to the conclusion, that innovativeness of Polish companies is at low to moderate level, hence it needs some support. This is rationale for formulating a proposal on enhancing innovativeness by cooperation, skills and competences flow between companies. The paper present both the rationale and the framework of the research project, striving for development of an IT tool/platform supporting innovative knowledge and skill transfer and absorption.


331. Skeleton-based Generative Modelling method in the context of increasing functionality of virtual product assembly

Andrzej Jalowiecki1, Pawel Klusek2, Wojciech Skarka1

1Silesian University of Technology, Poland; 2Key-Solutions, Ligocka Street 103, Katowice 40-568, Poland

Generative Modelling methods are becoming more popular. Despite the fast and dynamic development of CAx systems, well- described procedures of Generative Model creation do not exist. The lack of the described systems and their methodologies means that only a small group of engineers have knowledge and experience to create and use such type of models. In this paper, the authors try to highlight two methods of Generative Model preparation. These methods are the results of the authors’ experiences in working with such types of models. The first method is based on cooperation with external models which are input elements into a Generative Model. Input elements (geometrical or parametrical) are one of the most important things in the process of automatic model generation. The second described method is based on an input element in a wireframe form. The paper highlights areas of application and some advantages and disadvantages for each of the presented methods.

© 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing.

Keywords: Generative Modelling, Knowledge-Based Engineering, Skeleton-Based Design, CATIA V5


332. The methods of knowledge acquisition in the Product Lifecycle for a Generative Model’s creation process

Andrzej Jalowiecki1, Pawel Klusek2, Wojciech Skarka1

1Silesian University of Technology, Poland; 2Key Solutions, Ligocka Street 103, Katowice 40-568, Poland

The process of automation becomes popular at different stages of the Product Lifecycle. By applying advanced CAx systems and advanced modelling techniques such as a Generative Modelling, it is possible to design, manufacture and release products onto the market in an easy and fast way. During the Product Lifecycle, a lot of knowledge about the product is generated, however, in the standard process, this knowledge is lost. By using the Knowledge-Based Engineering technique, it is possible to capture, formalise and reuse the knowledge about projects in the future. This approach has a lot of advantages, which are described in this paper.


339. Managing collaboration of specialists in various areas – a multidisciplinary approach to human centered design

Ryszard Skoberla, Wojciech Skarka, Katarzyna Jezierska-Krupa

Silesian University of Technology, Poland

Problems we face nowadays often concern complex objects and systems. In order to acquire a full spectrum of their complexity and design possibilities, it is required to adopt a multidisciplinary approach at the very first stages of the design process, namely research and ideation. This will enable to use knowledge from different, seemingly not related, domains. That is a big challenge though, as it requires gathering and integration of information, requirements and constraints from many scientific fields, which sometimes happen to be ruled by conflicting priorities. In this article we make an attempt to analyze the influence of way of managing specialistic knowledge on the quality and diversity of ideas generated during ideation. We present a study of a role of multiple specialists participation in ideation process and the influence of design priorities they adopted on various ideation stages on the final outcome. For this purpose a method was elaborated, that allowed to examine these issues. It is based on performance comparison of four groups of students. Members of the first two groups were managed to focus on using specialistic knowledge (each member on different domain) at the very first stages of the design process. Members of the other two groups, on the other hand, were not assigned to any specific scientific area and explore the problem freely. Both groups were lead to use various tools and methods in order to gain a wide understanding of a problem faced. Next, they went through ideation process, based od C-Sketch method. Finally, they evaluated ideas generated in the process.

The paper compares two approaches to managing specialistic knowledge in the ideation process in relation to the multidisciplinary problems. It presents the analysis of advantages, disadvantages and threats resulting from the adoption of a specific approach. It may be a useful basis while making a decision to choose a method and a way of realization of the ideation process.


55. Location Independent Manufacturing – Case-based Blue Ocean Strategy.

Mika Lohtander, Antti Aholainen, Jarno Volotinen, Merja Peltokoski, Juho Ratava

Lappeenranta University of Technology, Finland

Environmental impact, saving natural resources and ecological behaviour are important factors for European manufacturing industry. Industry must concentrate to manufacture sustainable and recyclable products, but also the whole production processes have to be environment-friendly. Other important factors from a management point of view are ecological raw materials sourcing, ethical decision making and low emission delivery. Therefore, manufacturing companies are trying to arrange their manufacturing processes and facilities to correspond these demands. Other well-known current and future challenges are ageing, individualism, globalisation, urbanisation, and sustainability offer new finance possibilities but also a potential crisis. These global market’s megatrends have impacted to all manufacturing sectors and have caused a structural change in the manufacturing industry. Today’s industries are mostly pursuing towards knowledge in the global ICT globalisation and sustainability paradigms which are key factors in the competition for success between companies in the global economic. Globalisation, which is a key enabler of economic growth, is the most important benefit factor in the competition.

The LIM (Location Independent Manufacturing) concept has a partial answer for the challenges and needs presented by globalisation, sustainability, individualism and urbanisation megatrends. The LIM concept is a novel manufacturing and managing concept. It has been getting considerable attention lately in the Finnish manufacturing industry, especially among small and medium-sized enterprises. Besides its sustainability and environmental aspects, the LIM is an interesting concept since it contributes to the servitization paradigm and transformation towards industrial services.

The aim of this study is to build further understanding of the LIM by analysing an actual LIM-concept utilisation case with a company. The company that is the objective of this study supplies a wide range of wood processing production lines, machines and equipment tailored to customers’ needs. The company also provides solutions and cooperation via maintenance and life-cycle services. The operations use a project-based organisation close to the customers. The aim of the company is to improve the cost-effectiveness of their operations as well as increase their agility and strategic adaptability to respond to changing needs through new modifications of their machinery and products.

This study builds up how the Blue Ocean Strategy could help create new business opportunities to SMEs. Based on the case study, it has been analysed how to create uncontested market leadership by reconstructing market boundaries, how to focus on the big picture, how to go beyond existing demands, and finally how to get the correct strategic sequence. The study shows that many substructures of the LIM concept exist in the everyday business environment, but new understanding is needed to get the total benefit from the changing world.

 
2:20pm - 4:00pmSES 10.1: Robots in AVM
Session Chair: Giovanni Berselli
Aula Convegni (first floor) 
 

139. The WIRES Experiment: Tools and Strategies for Robotized Switchgear Cabling

Maurizio Busi1, Andrea Cirillo2, Daniele De Gregorio3, Maurizio Indovini1, Giuseppe De Maria2, Claudio Melchiorri3, Ciro Natale2, Gianluca Palli3, Salvatore Pirozzi2

1University of Bologna, Italy; 2Università degli Studi della Campania "Luigi Vanvitelli", Viale Abramo Lincoln, 5, 81100 Caserta, Italy; 3Università degli Studi di Bologna, Viale Risorgimento 2, 40136 Bologna, Italy

This paper presents the preliminary results obtained within the WIRES experiment. This experiment aims to automatize the switchgear wiring process by using industrial manipulators and properly designed hardware and software tools. The challenging objective of the experiment is the development of a proper computer vision algorithm able to detect the switchgear components and a novel gripper, with an integrated tactile sensor, able to manipulate wires and simultaneously operate on screw/clip type connection points. Another objective of the experiment is the development of a software package able to optimize the wiring sequence and to plan the robot trajectories, based on the CAD data coming from the switchgear design software. The concept of such a software tool is here presented.


195. Towards intelligent autonomous sorting of unclassified nuclear wastes

Andrea Basso1, Vasek Hlavak2, Jiri Hulka3, Michal Jilich4, Pavel Krsek2, Sotiris Malasiotis5, Rezia Molfino4, Vladimir Smutny2, Libor Wagner2, Matteo Zoppi4

1University of Genoa, Italy; 2Czech Technical University, Czech Institute of Informatics, Robotics and Cybernetics, 166 66 Prague 6, Zikova 4, Czech Republic; 3National Radiation Protection Institute, 140 00 Prague 4, Bartoškova 28, Czech Republic; 4Universita degli Studi Di Genova, Dept. of Mechanics and Machine Design, 16145 Genova, Via Opera Pia 15A, Italy; 5Center for Research and Technology Hellas, Information Technologies Institute, 6th km Xarilaou - Thermi, 57001 Thessaloniki, Greece

Sorting of old and mixed nuclear wastes for repackaging on the base of their intensity of radiation and compressibility has been presenting a process bottleneck that demands an active human involvement. The main one coincides with the operation of sorting itself: humans perform the picking and separation of the different materials using remotely operated arms and, either, see the scene from a single camera or look at it through a thick shielded glass. They have no or extremely poor depth perception and no tactile information. The job has been slow and tiring; shifts are short because the quickly incoming loss of attention may result in sorting mistakes and dramatic slow down; picking of small items such as tiny highly radioactive springs is achieved after several attempts. Consequently automation of the process is utmost desirable to reduce the operating costs, ergonomics and plant throughput. In the framework of the newly funded European project ECHORD++, experiment RadioRoSo, a pilot robotic cell is being developed and validated against industrial requirements on a range of sorting tasks. Off-the shelve industrial robots are involved, the dual-arm robot from past EC funded project CloPeMa. The custom gripper, vision feedback and new manipulation skills have been under development. This paper presents application context, cell layout and sorting approach.


211. Conceptual Design and Control Strategy of a Robotic Cell for Precision Assembly in Radar Antenna Systems

Riccardo Signore1, Stanislao Grazioso2, Antonio Fariello3, Francesco Murgia3, Mario Selvaggio3, Giuseppe Di Gironimo2

1MBDA Italia Spa, Via Carlo Calosi 105, 80070 Bacoli, Italy; 2Department of Industrial Engineering, University of Naples Federico II, P.le Tecchio 80, 80125 Napoli; 3Department of Information Technology and Electrical Engineering, University of Naples Federico II, Via Claudio 21, 80125 Napoli

Dip-Brazing is a metal-joining process in which two or more metal items are joined together using a low-temperature melting element as filler. In telecommunication field, this process is used to fabricate radar antenna systems. The process begins with the assembly of the parts constituting the antenna and the thin filler sheet used to join the parts. The mechanical deformations of the micro-pins of the parts allow to obtain a more compact mechanical assembly, before than the antenna system is subjected to an immersion cycle used for adjoining the parts. In this work, we present the design of the robotic cell to automate the assembly procedure in the aluminum dip-brazing of antenna in MBDA missile systems. In particular, we propose a robotic cell using two stations: i) assembly, using a SCARA manipulator; ii) riveting, using a three-axis cartesian robot designed for positioning a radial riveting unit. Motion control of the robots and scheduling of the operations is presented. Experiments simulated in a virtual environment show an almost perfect tracking of the designed trajectories. The standardization of the procedure as well as the reduction of its execution time is thus achieved for the industrial scenario.


292. Micro-robotic handling solutions for PCB (re-)manufacturing

Serena Ruggeri1, Gianmauro Fontana1, Vito Basile2, Marcello Valori2, Irene Fassi1

1Institute of Industrial Technologies and Automation, National Research Council, Via A. Corti, 12, 20133 - Milan, Italy; 2Institute of Industrial Technologies and Automation, National Research Council, Via P. Lembo, 38/F, 70124 - Bari, Italy

In the last decades, electronic products have been widely investigated, leading to the development of enabling technologies, processes and devices in many fields, including smart manufacturing, automotive, aerospace, and biomedical. Their progressive miniaturization calls for smaller and smaller components integrating an increasing number of functionalities. Moreover, the trend towards the miniaturization requires the optimization of the PCB (Printed Circuit Board) structure and components layout.

This approach is very beneficial in terms of achievable performance; however, due to the large amount of PCBs in different products, new issues related to the remanufacturing and reuse of the end-of-life products arise. Recent industrial trends strongly promote these concepts as paradigms of the so called “circular economy”.

This scenario introduces further challenges, related to demanding specifications, to be addressed with enhanced or new (re-)manufacturing processes, innovative devices and tools, and advanced strategies, on which several research groups investigate, proposing different solutions. In the (re-)manufacturing processes of PCBs, the manipulation of micro-components requires high precision, reliability and high throughput, that are difficult to be achieved at the micro-scale due to the adhesion forces often hindering the process, therefore limiting the overall performance of the conventional systems.

In this context, the current paper discusses some challenging applications exploiting novel automatic solutions on different complexity levels of the process, from the component to the whole system, including devices, tools and robotized work-cells. These applications include the reballing of BGA (Ball Grid Array) packages for the remanufacturing process, the precise positioning of SMT (Surface Mount Technology) components in PCB structures such as conventional rigid planar PCB (2D packaging technology) or innovative embedded PCB (3D packaging technology), inspection and quality control.

The paper discusses the precise manipulation of components, such as SMD resistors and capacitors with sizes down to 0.2 x 0.125 x 0.125 mm, as well as sorting and positioning of solder balls with diameter ranging from 0.3 to 1 mm on BGA package surfaces.

Different approaches and solutions are reviewed including a vacuum micro-gripper integrating an innovative release system and a store-and-place device, able to single-sort micro-spheres with high throughput. Both the types of tools have been prototyped and tested and compared with conventional commercial tools.

At a work-cell level, two systems are discussed: the former, in accordance to the micro-factory paradigm, represents a vision-based robotized micro-manipulation and assembly work-cell; the latter includes a collaborative robot able to safely interact with the human operator and other robots for the handling and inspection of components. Finally, at a factory level, these two work-cells have been integrated to set up a pilot plant to support different PCB remanufacturing phases.


179. Virtual Prototyping of a Flexure-based RCC Device for Automated Assembly

Valerio Vaschieri2, Michele Gadaleta2, Pietro Bilancia1, Giovanni Berselli1, Roberto Razzoli1

1Univeristy of Genoa, Italy; 2nzo Ferrari” Department of Engineering, University of Modena and Reggio Emilia, Via P. Vivarelli, 10, 41125 Modena, Italy

The actual use of Industrial Robots (IR) for assembly systems requires the exertion of suitable strategies allowing to overcome shortcomings about IR poor precision and repeatability. In this paper, the practical issues that emerge during common "peg-in-hole" assembly procedures are discussed. In particular, the use of passive Remote Center of Compliance (RCC) devices, capable of compensating the IR non-optimal performance in terms of repeatability, is investigated. The focus of the paper is the design and simulation of a flexure-based RCC that allows the prevention of jamming, due to possible positioning inaccuracies during peg insertion. The proposed RCC architecture comprises a set of flexural hinges, whose behavior is simulated via a CAE tool that provides built-in functions for modelling the motion of compliant members. For given friction coefficients of the contact surfaces, these numerical simulations allow to determine the maximum lateral and angular misalignments effectively manageable by the RCC device.

 
2:20pm - 4:00pmSES 10.2: Production Planning and Scheduling
Session Chair: Sang Won Yoon
Aula N (first floor) 
 

201. Using simulation to analyze picker blocking in manual order picking systems

Behnam Bahrami2, El-Houssaine Aghezzaf2, Veronique Limere1

1GENT UNIVERSITY, Belgium; 2Department of Industrial Systems Engineering and Product Design

The rise of the e-commerce practice makes the warehouses be confronted with ever smaller orders that must be met ever faster, often within a 24-h period. This pressures the order picking process as the orders pickers’ workload becomes higher and higher, leading subsequently to congestion in the warehouse and impacting its productivity. It is therefore crucial to determine which order batching and picking policies enhance the performance of order picking activities. This paper carries out an intensive simulation study to examine the performance of different order picking policies with batching in a wide-aisle warehouse with a low-level picker-to-parts system. The performance of the system is measured in terms of total traveled distance, number of collisions between operators (congestion) and order lead times. A full factorial design is set up and the simulation output is statistically analyzed. The results are reported and thoroughly discussed.


130. Job shop flow time prediction using neural networks

Cristovao Silva, Vera Ribeiro, Pedro Coelho, Vanessa Magalhaes, Pedro Neto

University of Coimbra, Portugal

Due date assignment is a complex process of major importance for shop floor control. Quoting realistic due dates and delivering the goods on time allow to enhance customer service and to improve resource utilization by making it more efficient.

The due date assignment problem is intimately related to the problem of flow time prediction. If flow time prediction were perfect, the due date assignment problem would be greatly simplified because completion dates for jobs would be known. Unfortunately, flow time prediction is a challenging task, essentially in dynamic job shops in which jobs arrive at the shop over time. In this case, each arriving job has its own processing needs, in different machines and it will experience different congestion levels. Furthermore, if the shop dispatching rule is not “first in first out”, the arrival of a new job can change the processing sequence and thus the expected completion dates of jobs already in the system.

Flow time prediction is a difficult task due to the number of non-linear related aspects that can affect it. In this study we investigate how Artificial Neural Networks (ANN) can be used as a flow time prediction method.

To evaluate the ability of the proposed model to correctly predict job flow times, a simulation model of a dynamic job-shop was developed to generate the necessary data to train and test the ANN. Since the dispatching rules, adopted in the shop, can affect the flow time of the orders two scenarios are considered: (1) jobs are prioritized according to the First in First Out rule and (2) jobs are prioritized according to the Shortest Processing Time rule.

Results obtained with the proposed ANN flow time prediction model are compared with results obtained by two dynamic due date setting rules proposed in the literature: (1) the Dynamic Total Work Content (DTWK) rule and (2) the Dynamic Processing Time Plus Waiting (DPPW) rule. Results are compared considering three performance measures usually used to evaluate flow time prediction accuracy: Mean Absolute Lateness (MAL), Percentage of Tardy Jobs (PT) and Mean Tardiness (MT).

Results show that the proposed ANN model performs better than DTWK and DPPW rules independently of the used dispatching rules, for all the performance measures considered. Thus, if the shop information is easy to obtain, ANN can be used to predict job flow time and consequently to assign reliable due dates.


68. Process planning in Industry 4.0 environment

Maja Trstenjak, Predrag Cosic

Faculty Of Mechanical Engineering and Naval Architecture, Croatia

World is currently facing the fourth industrial revolution. Working environment is demanded to be changed, rapidly, with hope that it will bring significant benefits in the future. Usual manufacturing processes are being automatized and connected to other activities within the company. One of the most important factors in Industry 4.0. environment is data management, big data management to be correct. It is done with use of cyber-physical systems, internet of things and cloud computing. Human professions are obligated to adapt and change so the roles that are known are suggested to get a different structure in the future. Workers have to learn to deal with new situation and accept the term of life-learning process, constantly improving their performance. In the end, with use of both technological and human improvements, bigger productivity, product quality and income with lower product delivery (manufacturing) time and product price are expected.

This paper will deal with change the role of process planner who will be presented as "product planner" in the environment of Industry 4.0. Product planner will use advanced process planning methods and will manage product and feedback database. Product database is some sort of archive of previously manufactured products and feedback database is collection of data from various sources within product supply chain. Feedback database helps to improve the process planning that results with product of higher quality. It allows the product planner to connect with other parts of the company and to be acknowledged with customer feedback. Among mentioned, overall working sphere of the new role will be presented in the paper.


96. Mapping the conceptual relationship among data analysis, knowledge generation and decision-making in industrial processes

Cleiton Ferreira dos Santos, Flávio Piechnicki, Eduardo de Freitas Rocha Loures, Eduardo Alves Portela Santos

Pontifical Catholic University of Parana, Brazil

Due to the development of information technology, monitoring and control systems have been boosted to increase their ability to collect, process and manage data in industrial processes. Increasing information complexity makes it difficult to organize and understand the large volume of data created under different operating and maintenance decision perspectives. The information flow and integration of the systems involved is a theme in the recent development of Industry 4.0, since that many records are being generated, but just a little knowledge is being explored. In this scenario, Data Engineering and Analytics concepts stand out, aiming the analysis and conversion of data stored in knowledge through different techniques, such as Knowledge Discovery in Databases (KDD), Data Mining (DM) and Process Mining (PM). Although it is possible to extract knowledge from the database (quantitative knowledge) through these techniques, the decision making involved in the industrial processes are still very dependent on the tacit knowledge of the operator (qualitative knowledge). In this environment characterized by information heterogeneity and complexity, Multi-Criteria Decision Making/Analysis (MCDM/A) methods present an appropriate approach to assisting operators in information processing and standardization for more assertive and effective decision-making. These methods include the Analytic Hierarchy Process (AHP), Technique for the Order of Priority for Similarity to Ideal Solution (TOPSIS), ELimination and Choice Expressing Reality (ELECTRE TRI) and The Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE). All of them aim to suggest an alternative of choice among several available, based on multiple criteria conflicting in the decision-making. In the literature, quantitative and qualitative approaches are dissociated in the process of knowledge extraction and decision-making, identifying an important gap. Therefore, this paper aims to develop a conceptual map that relates these major areas of knowledge – data analysis, knowledge generation and decision-making. A focal analysis is given to the MCDM/A and Process Mining methods, facilitating the decision-making process supported by data from the factory floor through process models. Through process mining, it is possible to identify and analyze process models considering the moment in which each record occurred (timestamp), its frequency (weight), extracting information and performance metrics. This quantitative information, together with qualitative evaluation criteria, finds in MCDM/A methods a basis of conciliation and informational treatment for analysis and decision-making. The objective is to highlight the way in which conciliation and the decision-making process can occur through conceptual maps that organize the knowledge involved. The results obtained from this analysis will provide important clues for the design of information systems in support of an industrial management that adheres to the requirements of Industry 4.0.


33. Evolutionary Algorithms for Programming Pneumatic Sequential Circuit Controllers

Sajaysurya Ganesh, Saravana Kumar Gurunathan

Indian Institute of Technology Madras, India

Sequential actuation of pneumatics is a common form of automation in small and medium scale industries. Changing the sequence of actuation of a given set of cylinders, by changing the logic program of actuation, based on the type of product being produced, is an economical technique to implement flexible automation in such industries. Even though the logic program for sequential actuation of cylinders based on the state of end-position sensors is stored in programmable logic controllers (PLC), the techniques for deriving logic equations (and corresponding PLC programs) has largely remained manual, and has hindered the implementation of flexible automation. Recently, the authors have published techniques to automatically convert a sequence of cylinder actuation into a truth-table using Genetic Algorithm and have suggested using algorithms like Quine-McCluskey for converting truth-tables into logic equations. However, Quine-McCluskey algorithm is NP-Complete and can adversely affect the changeover time in a large flexible automation setup. Hence, in this paper, the authors have addressed the problem of converting a truth-table into corresponding logic equations using Genetic Programming, that promises much quicker solutions for difficult problems. A modified Genetic Programming with elitism was developed specifically for this application and its capabilities has been demonstrated through case studies. Further, a methodology for optimizing the parameters of Genetic Algorithm that converts actuation sequence into truth-table has also been proposed which can further reduce the changeover time. Together, these techniques will provide an efficient way to modify existing fixed automation setups and implement flexible automation in small and medium scale industries.

 
2:20pm - 4:00pmSES 10.3: Lean and Agile Manufacturing
Session Chair: F. Frank Chen
Aula O (first floor) 
 

302. Application of Lean Production Principles and Tools for Quality Improvement of Productive Processes in a Carton Company

Cristina Roriz1, Eusébio Nunes2, Sergio Sousa2

1University of Minho, Portugal; 2ALGORITMI Research Center, University of Minho - DPS, 4710-057 Braga, Portugal

1. Introduction

In general, companies are under pressure to improve productivity and quality while reducing costs. This has led many of these companies to implement a Lean Production philosophy [1]. Lean Production is a multidimensional approach that covers a variety of management practices that aim to reduce waste and improve operational effectiveness [2]. However, the application of the practices alone does not ensure the implementation of the Lean philosophy. In addition to technical factors, non-tangible change factors, such as creating a supportive learning environment and developing leadership in the organization are required. Other companies follow a different strategy and use quality continuous improvement of products / services.

In this context, a management strategy that combines TQM principles with Lean Production principles has proved to be adequate for many companies [3].

This study was carried out in a company of the sector of the production of corrugated cardboard boxes and lithographic boxes, having as main objective quality and performance improvement of a production process applying TQM and Lean Production principles and tools.

2. Methodology

The methodology used in this work can be structured in the following steps:

1: Analysis of the productive system and survey of potential problems that affect its performance; Identification of sub-process or critical operations for process performance;

2: For the sub-process or critical operations identified in step 1, conduct in-depth analysis and diagnosis to assess key issues and identify root causes of these problems. If necessary, establish performance indicators, create record sheets, collect data and evaluate performance indicators;

3: Presentation of proposals to solve the problems identified in step 2;

4: Analysis and selection of proposals to be implemented and implementation planning;

5: Implementation of proposals, evaluation of their effectiveness and planning and implementation of possible corrective measures.

3. Results and Discussion

The “crosslinking” section was identified as the section that most contributes to the production of nonconformities throughout the process. The analysis of the current situation of this section was carried out using the cause-effect diagram, Pareto’s analysis, study of setup times, and also the creation of some performance indicators such as Overall Equipment Effectiveness (OEE) and waste quantification.

4. Conclusions

The proposed method identified the main operational problems, such as high setup times, low availability of machines, lack of organization in the working area, etc. To solve these problems, improvement proposals, based on Lean Production, were presented, like the implementation of the SMED (Single Minute Exchange of Die), 5S technique and visual management, having resulted in a reduction of 23% in the setup time and a reduction of 60% in the movements carried out by the operator.

5. References

[1] J. Liker, “The Toyota Way”, Madison, WI, McGraw-Hill, 2004.

[2] J Womack, and D Jones, “Lean Thinking”, New York, NY, Free Press, 2003.

[3] N. Salleh, K. Salmiah and H. Jaafar, Review study of developing an integrated TQM with LM framework model in Malaysian automotive industry, TQM Journal, Vol. 24, Issue 5, p399-417, 2012.


40. Lean manufacturing applied to metallic wire rope assembly lines for automotive industry

Maria Conceição Rosa, Francisco J. G. Silva, Luís Pinto Ferreira

Isep, Portugal

The automotive industry is one of the most demanding sectors in the global market, since it requires a systematic increase in productivity. In the current economic scenario, the challenges at hand are great: the reduction of costs and an increase in competitiveness, without investment. In order to address this situation, the only solution resides in the optimization of the product and/or processes.

This study was developed at the FICOCABLES company, where one sought to improve the assembly lines of the metallic wire ropes used to control some of the basic functions in cars, such as elevating car-door windows, opening car and fuel-tank doors, and so on. As in any other company dedicated to the production of automotive components, improvements aimed at increasing the competitiveness of this type of product are extremely welcome; any kind of disturbance in the production flow can cause serious problems in the supply chain, as well as in the final car assembly lines.

The work began with an extensive study of the shop-floor, so that one could map out the processes involved in the assembly line, the respective technologies involved, task registration and the collection of production times for each line. In order to identify both the problems and difficulties which cause waste of time and money in the value chain, corresponding Value Stream Mapping (VSM) was used to evaluate the current state. One resorted to Lean tools so as to eliminate waste and maximize earnings, and new solutions were studied for the identified problems. By applying the PDCA methodology based on an action plan, one was able to ensure the implementation of some solutions, as well as the subsequent processes and the registration of these for future memory.

The performance of efficiency was dramatically increased by this study. It allowed one to determine that the application of this methodology to other assembly lines is crucial, when attempting to improve overall efficiency. The result is the achievement of effective productivity earnings, making the assembly lines more profitable, or allowing for a drop in product cost. The overall quality was also greatly increased in this manner.


2. Lean Production Training for the Manufacturing Industry: Experiences from Karlstad Lean Factory

Leo J. De Vin, Lasse Jacobsson, Janerik Odhe, Anders Wickberg

Karlstad university, Sweden

Introduction

Simulation for training lean manufacturing ranges from simple paper-based or LEGO®-based games to larger scale simulation environments, for instance push car assembly. This may be suitable for educating students, but often less so for training industry workers. The latter group typically is more diverse and is more used to intuitive learning than to formal instruction. Thus, it is important that a training environment for this group more realistically represents the work environment. For this reason, a lean training environment “Karlstad Lean Factory” that includes materials processing stations as well as assembly areas was created.

Serious Gaming Theory

Serious gaming theory is not always very suitable to describe lean production training for factory workers. Serious gaming theory often focuses on computer-based games. Often, it focuses on university students and/or military personnel as participants. These groups are not representative for factory workers. For instance, they usually are more homogeneous groups and formal training/education is part of their daily routine.

In the paper two new models are presented that are more suitable to describe Lean Production training. One describes the relationships between the work environment and the training environment. It highlights the importance of the participant group when designing a training environment. The second model describes the lean training activity. This model highlights the importance of debriefing, peer discussion, and change decision.

Karlstad Lean Factory

The single unit and batch processing stations of Karlstad Lean Factory are all equipped with stack lights. Processing times, breakdown intervals, and repair times can be set by the instructor. Thus, a variety of production environments be emulated, and it also allows for adjusting the level of difficulty to the participants’ proficiency. The Instructors can define a number of different rules for batch processing stations so as to emulate different production scenarios. The stations are easy to transport which facilitates on-site training if requested by a company.

First findings

At the time of abstract submission, Karlstad Lean Factory is being tested with industrial participants after functional tests with university students had been completed successfully. The full paper will report on first findings from these training sessions.

Future Research

An initial comparison between usually relatively homogeneous groups such as university students or military personnel and often more heterogeneous groups such as industrial employees has resulted in five hypotheses to be studied in future research:

1) For heterogeneous groups (which factory workers often are), training transfer may vary significantly, even within one group of participants.

2) In the low- to medium simulator fidelity range, factory workers need more similarity between the work environment and the training environment to get the same amount of training transfer.

3) Factory workers require a higher degree of similarity (fidelity) for training transfer to take place at all.

4) For high fidelity simulation environments, factory workers have concrete work experience that they can relate to, and training transfer surpasses that for university students.

5) For novices in manufacturing, high fidelity simulators are not very suitable. They are too complex for novices.


173. Interdependencies of Industrie 4.0 & Lean Production Systems – a use cases analysis

Uwe Dombrowski, Thomas Richter, Philipp Krenkel

TU Braunschweig, Germany

Lean has become a widely spread approach to gain high efficient processes in enterprises. Nowadays, Industrie 4.0 is one of the most promising approach to cope future challenges in the production environment. It is shown, that a process orientated organization and thus, Lean Production Systems might be an enabler towards a successful and sustainable implementation of Industrie 4.0 in the production environment. [1] To enable a detailed analysis of interdependencies between Lean Production Systems (LPS) and Indstrie 4.0, several Industrie 4.0 elements have been structured into technologies, systems and process related characteristics, based on 260 use cases of applied Industrie 4.0 technologies in the German industry. Afterwards, the use cases have been analyzed regarding interdependencies between Industie 4.0 and principles of Lean Production Systems.


57. Lean information and communication tool to connect shop and top floor in small and medium-sized enterprises

Rainer Müller, Matthias Vette, Leenhard Hörauf, Christoph Speicher, Dirk Burkhard

ZeMA - Zentrum für Mechatronik und Automatisierungstechnik gGmbH, Germany

Small and medium-sized enterprises (SME) see themselves confronted with constant challenges. Globalization, volatile markets and international competition require a focus on key topics such as customer satisfaction and delivery reliability. Key requirements for achieving these aims are lean and reactive business processes, which are obtained through horizontal and vertical networking of shop floor and top floor.

The Industry 4.0 research project NeWiP deals with, amongst others, integrated information networking in small and medium-sized enterprises, in the sector of custom machine engineering. In these companies, information acquisition and transmission is carried out mainly in a paper-based way. An application scenario for example, is the modification process of technical drawings under consideration of business processes. Skilled workers and foremen are qualified to make necessary modifications during the manufacturing and assembly process on the shop floor. The modifications are outlined by hand in the technical drawing. At the end of the production process, all technical drawings are passed over to the construction/development department, in order to create an overall documentation. Due to the fact that all technical drawings are passed to the construction/development department simultaneously, and therefore have to be reworked successively, there is an extension of both the completion time and the project term. At the same time, handwritten modifications of technical drawings increase both the risk of media disruption between shop floor and the construction/development division on the top floor as well as the total costs.

This paper presents, by means of the above-mentioned scenario, a production application for gathering and needs-based communication of part modifications in technical drawings by smart devices. The application focus different organization units and business processes, with the aim to digitalize the previously described analog processes and avoid media disruption in the company. The paper deals with the following steps: analysis and development stages of the production app, smart devices and implementation of the system on the shop floor.

 
2:20pm - 4:00pmSES 10.4: Engineering Collaboration for Smart Manufacturing
Session Chair: Josip Stjepandic
Aula P (first floor) 
 

250. Purchasing Management: The Optimisation of Product Variance

Christian Josef Uhl1, Farhad Nabhani1, Florian Kauf2, Alireza Shokri3, David Hughes1

1School of Science and Engineering, Teesside University, Middlesbrough, TS1 3BA, UK; 2School of Technology, Economy and Social Policy, Ravensburg-Weingarten University, GER; 3Department of Operations, Logistics and Supply Chain Managemen,t University of Northumberia, Newcastle, UK

The purpose of this paper is to present a new optimised approach for product and process variance from the purchasing perspective. The research is based on two case studies involving a global acting automotive Tier 1 supplier who produces steering systems for cars and commercial vehicles. The first case study analysis the product variance of three components. The data were gathered from 116 variants, 13 sub suppliers for three different types of steering system. The second case study presents the conflict between the digitalisation of the sourcing process and the creation of unnecessary variance through the number of suppliers. The sourcing processes of a total of 50 different single components from an automotive steering system were analysed and evaluated. Time, money, quality and technology can be saved through a greater understanding of such product and process variances. The results of the case studies lead to a generalised method to optimise the existing variance, present cost improvements as well as optimising new key performance indicators to manage product and process variance out of the purchasing department.


143. Advances in 3D Measurement Data Management for Industry 4.0

Christian Emmer1, Kai-Henry Glaesner2, Alain Pfouga1, Josip Stjepandic1

1PROSTEP AG, Germany; 2Daimler AG, Stuttgart, Germany

This paper provides a novel approach for comprehensive 3D measurement data management in complex process chains in the automotive industry to fulfill technological requirements of Industry 4.0.

A variety of measurement methods and equipment are used in the automotive industry today to ensure the specified level of product quality. The multitude of devices and processes found in the automotive industry has always provided fertile ground for the harmonization of processes and methods. The desire for a standardized interface for the flexible design of the measurement process, is therefore a logical consequence. It requires a complex object model that not only includes the product model but also the equipment and tools, as well as the relevant test and tolerance data (product and manufacturing information and its relation to the 3D geometry).

Cross-domain data management also gives rise to the need for powerful measurement data management. Here, factors such as data-related recording, digital master, and control of the measurement process, as well as IT systems and interfaces play a role. Companies are hoping that this will bring about an increase in the level of process automation, improvements to the change process, further stabilization in the process, consistent quality statements, enhanced performance in individual process steps, as well as the early identification of risks. This challenge was recognized a number of years ago and was taken up by the Inspection PlusPlus Data Management Services (I++ DMS) initiative, a consortium of European automobile manufacturers.

Initial implementations of I++ DMS are being used in the quality management systems operated by German automotive OEMs. The data is not typically exchanged directly between the data-producing and the data-consuming systems but rather via an intermediate layer for persistent data storage. I++ DMS has not yet been able to sufficiently establish itself as a standard in the extremely complex measurement process. Implementation of the measurement process involving many different manufacturers and components is therefore still being stretched to the limit – a limit that would vanish with the definition of a uniform interface.

A project group entitled “3D Measurement Data Management“ was set up under the joint auspices of the VDA (German Association of the Automotive Industry) and the ProSTEP iViP Association in order to address this issue. It is evaluating the current status of I++ DMS with regard to its suitability as the standard format.

The reference process created within the framework of the working group comprises not only inspection planning but the entire process chain: quality assurance, inspection plan, inspection task, and measurements. The group is focusing on two use cases: the process chain involved in exchanging quality data within a company and the exchange of quality data between an OEM and a supplier.

The findings and results of this working group have a tremendous relevance to introduction of Industry 4.0 in complex manufacturing processes. It is contribution to optimization of existing equipment as well as development of new equipment in the areas measurement strategies, measurement principles and evaluation rules.


144. Agile Digitale Transformation of Enterprise Architecture Models in Engineering Collaboration

Sergej Bondar1, John C. Hsu2, Alain Pfouga1, Josip Stjepandic1

1PROSTEP AG, Germany; 2California State University Long Beach, USA

Emergent behavior is behavior of a system that does not depend on its individual parts, but on their relationships to one another. Such behavior exists in biological systems, physical systems as well as in the human performance. It is an inherited nature of a System-of-Systems (SoS). A suitable framework is needed to guide the development of SoS architecture, which includes emergent behavior. Enterprise architecture (EA) is a discipline driving change within organizations. Aligning and integrating business and IT thereby belongs to strategic management. The management of EA change is a challenging task for enterprise architects, due to complex dependencies amongst EA models, when evolving towards different alternatives. In this paper, various architecture frameworks are explored for an application on SoS architecture: the Department of Defense Architecture Framework (DoDAF) and Ministry of Defense Architecture Framework (MODAF) are declared inappropriate. The Open Group Architecture Framework (TOGAF), the Federal Enterprise Architecture Framework (FEAF) and the Zachman Framework on the other hand are suitable. The use of Zachman Framework to guide the architecture development is described in step-by-step details in this paper. The agent-based simulation is recommended to develop the SoS architectural models following the Zachman Framework guidance.

Zachman framework has gained a high importance in large companies. Question arises how it can be applied to SME, in particular with the collaborative engineering. As two concurrently emerging topics, the enterprise architecture (EA) and the digital transformation (DT) affect each other. Within SME, the adoption of enterprise architecture heavily depends on the position of the business owners and business leaders respectively. In the most cases, they are satisfied with an optimized workflow management. Process definitions according to TOGAF are on a very abstract level and provide solely an informal guidance that can be used as a starting point for further refinement in organizations. As a matter of fact, a SME is acting agile and flexible, and don’t accept formalism easily.

OpenDESC.com is an industry-focused portal for engineering collaboration with features serving especially automotive throughout an extended enterprise. It is a holistic service, which includes both translation of engineering data into a custom environment and secured provision of engineering data to partners in an automotive SoS. The conception consists of a high-level architecture of the platform on the perspective of 6 selected layers of the Zachman Framework. We have investigated the emergent behavior of this architecture which is expected to be easy to adapt and transform for development of new services.

The findings and results of this research have a significant relevance to implementation of Digital Transformation in the complex global operations. It is contribution to coherence of Enterprise Architecture and agile Digital Transformation in development of new solutions and services.


216. The role of business relationships in new product development. The case of Antrox-Nel Design

Maura Mengoni1, Andrea Perna2, Maurizio Bevilacqua1, Luca Giraldi1

1Università Politecnica delle Marche, Italy; 2Department of Engineering Sciences, Division of Industrial Engineering & Management, Uppsala University, Uppsala, Sweden.

This paper focuses on the study of a new product development process in business-to-business setting. By adopting a case study research strategy, the main findings show how the evolution of a business relationship influences the whole product development process. The research also clearly shows how business relationships initiated from pre-existing social relationships tend evolve continuously, better adapting to the external environment and regenerating more easily compared to relationships established just for economic exchange. In addition, a novel product has been conceived that integrates lighting and architectural elements and exploiting a shared model of production. The result is an enrichment of design values and an increase of both turnovers.


217. Opportunities Assessment of Product Development Process in Industry 4.0

Kassio Santos, Eduardo Loures, Flavio Piechnicki, Osiris Canciglieri

Pontifical Catholic University of Paraná - PUCPR, Brazil

The current globalization is causing to the world economy a profound process of change. Companies have sought to apply strategies to minimize the negative environmental impacts of their products and processes, at the same time intensify their competitiveness. One of the differentials of the companies are the early launch of the products and the ability to the develop them, with the objectives to meet the growing needs and expectations of the customers. The product lifecycle is getting shorter, which encourages the continued flow of new product development projects in the industry. With intelligent factories and products, changes will happen in the way the products will be manufactured, impacting on various market sectors. Products customization by consumers, tends to be one more variable in the manufacturing process, and smart factories will have to be able to customize what each customer have into consideration, adapting to their preferences. Currently, the industrial value creation in the industrialized countries is shaped by the development towards the fourth stage of industrialization. The so-called Industry 4.0 is based on the establishment of smart factories, smart products and smart services embedded in an internet of things and of services also called industrial internet. The use of Artificial Intelligence tools for product and process development and the growing analysis of opportunity provoked by Industry 4.0 are increasingly presents. A research question then arises: How is the relationship between the Product Lifecycle Management and the fourth industrial revolution area? With this regard, this paper will present a state of the art review of Industry 4.0 based on recent developments in research and practice within PLM domain. Subsequently, an overview of different opportunities for product lifecycle management in Industry 4.0 will be presented. A multi-criteria decision making approach using the Analytic Hierarchy Process (AHP) is proposed in order to organize the knowledge and evaluate the relations between the concepts from the domains. As outcome, an overview of different opportunities for product lifecycle management in Industry 4.0 will be presented and a model will be proposed in order to relate the concepts.

 
2:20pm - 4:00pmSES 10.5: Training, Education and Innovation
Session Chair: Barbara Motyl
Aula Q (first floor) 
 

174. Training advanced skills for sustainable manufacturing: A digital serious game

Stefano Perini1, Rossella Luglietti1, Maria Margoudi2, Manuel Oliveira3, Marco Taisch1

1Department of Management, Economics and Industrial Engineering (DIG) - Politecnico di Milano, via R. Lambruschini4/b, 20156 Milan - Italy bHighSkillz Ltd,; 2F4 Admirals Offices, Main Gate Road - The Historic Dockyard Chatham, ME4 4TZ Kent - United Kingdom; 3Department of Industrial Management - SINTEF Technology and Society, P.O. Box 4760 Sluppen, NO-7465 Trondheim - Norway

Despite its rapid development towards the vision of Industry 4.0, the manufacturing sector is facing a serious lack of skilled human resources. As a consequence, considerable efforts should be done in order to update and improve the manufacturing skills of young generations and to prepare them to the challenges of the new industrial world. For this reason, the paper first identifies the learning requirements for the education and training about advanced manufacturing topics and the most suitable educational approaches to satisfy them. Among them, digital game-based learning (DGBL) is identified as one of the most promising and discussed in detail. On this basis, the Life Cycle Assessment (LCA) Game, a digital game (DG) aiming at supporting the comprehension of LCA for sustainable manufacturing, is presented together with the co-design process that was adopted in order to implement it. Thanks to its high scalability and focus on the practical implications of the use of LCA in an industrial context, the suitability of LCA Game for both universities and companies is shown. Finally, the potentialities of digital game-based learning applications for manufacturing as well as current limitations and directions for future research are discussed.


142. How will change the future engineers' skills in the Industry 4.0 framework? A questionnaire survey

Barbara Motyl1, Gabriele Baronio2, Stefano Uberti2, Domenico Speranza3, Stefano Filippi1

1Università degli Studi di Udine, Italy; 2DIMI Dept. University of Brescia, Brescia, Italy; 3DICEM Dept., University of Cassino and Lazio Meridionale, Cassino, Italy

Industry 4.0 represents one of the most challenging themes for engineering design an also for the engineering education framework. There are already some studies in the field of engineering teaching that aim to investigate how the educational needs of students and of the industrial workforce are changing. On this basis, this research wants to investigate what are the necessary skills and expertise to provide to young engineers to get ready for the Industry 4.0 framework. In particular, a questionnaire was used to analyze this situation. It was administered to students enrolled in the first and second year of the engineering undergraduate degrees held in three Italian universities: Brescia, Udine and Cassino. During two different academics years, a total of 463 students participated to the survey. The proposed questions were aimed to investigate some key issues of Industry 4.0, and the students’ digital belief and behaviors at their entrance in the university education system. The collected answers provided a picture of the actual situation in these three universities with some relevant considerations about engineering education. So, the fundamental question that authors want to answer is “Are we effectively ready for Industry 4.0 or do we still work on it?”


166. On the evolution of regional efficiency potentials

Benjamin Kuch1, Engelbert Westkämper2

1Graduate School of Excellence advanced Manufacturing, Engineering (GSaME) – University of Stuttgart Allmandring 35, 70569 Stuttgart, Germany; 2nstitut für Industrielle Fertigung und Fabrikbetrieb (IFF) – University of Stuttgart Nobelstr. 12, 70569, Stuttgart, Germany

In the presented article, business organizations are regarded as knowledge processing socio-technical systems which are confronted with challenges stemming from digitization. These systems involve both physical entities and social relations, and most of the current approaches on Industry 4.0 are putting emphasis on the technical side while neglecting the process of decision making. This article offers a perspective on efficiency potentials within a region, drawing on an evolution metaphor in order to argue for the need of a new management framework. This framework is to be based on a technological platform in order to facilitate coordination.


136. Competence Center for the Digital Transformation in Small and Medium-sized Enterprises

Egon Müller, Hendrik Hopf

Mittelstand 4.0 Competence Center Chemnitz, c/o Chemnitz University of Technology, Germany

The approaches of the internet of things, cyber-physical systems and industry 4.0 include various potentials for industrial enterprises. Thus, custom-designed goods can be produced rapidly and flexibly in small quantities. Comprehensive services around the product become more and more important in this context. The horizontal and vertical integration of business and technological processes in and between companies represents the basis for this digital transformation. This leads to fundamental changes in production and work processes. As a consequence, it is necessary to transfer knowledge and experiences from research & development into practical usage. The “Mittelstand 4.0 – Digital Production and Work Processes” initiative by the Federal Ministry for Economic Affairs and Energy in Germany supports small and medium-sized enterprises (SME) to become digitized, to network and to start using industry 4.0 applications. The “Mittelstand 4.0 Competence Center Chemnitz” is part of this initiative. It provides information, practical trainings, test environments and demonstrator projects for the SME in the region. In the paper, the center’s goals, structures and deliverables for SME are described.

 
2:20pm - 4:00pmSES 10.6: AR Applications in Industry 4.0
Session Chair: Antonello Uva
Aula R (first floor) 
 

177. From paper manual to AR manual: do we still need text?

Michele Gattullo1, Antonio E. Uva1, Michele Fiorentino1, Giulia Wally Scurati2, Francesco Ferrise3

1Politecnico di Bari, Italy; 2Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy; 3Department of Mechanics, Politecnico di Milano, Via La Masa 1, 20156 Milano, Italy

In this work, we studied the issue of the conversion of a traditional maintenance manual into an Augmented Reality manual. One of the advantages of the use of Augmented Reality to display technical instructions, respect to paper or computer assisted manual, is the reduction of text needed. In fact, most of technical information can be conveyed through other means such as CAD models, graphic signs, images, etc.. However, two questions remain open: 1) how to determine which instructions, or portion of them, can be converted into AR without using text; 2) how to reformulate the remaining instructions. In this work, we answered to these questions. As to the first one, we described an approach that allows to classify technical instructions into three categories. It is based on the analysis of the main verbs used in the instruction. This classification would help to reduce the effort in the authoring phase of an AR manual. As to the second question, we explored the possibility to use a Controlled Natural Language (CNL) to simplify the definition of new instructions and let them easier to translate into other languages.


147. Human-machine collaboration in virtual reality for adaptive production engineering

Andrea de Giorgio, Mario Romero, Mauro Onori, Lihui Wang

KTH, Royal Institute of Technology, Sweden

This paper outlines the main steps towards an open and adaptive simulation method for human-robot collaboration (HRC) in production engineering supported by virtual reality (VR). The work is based on the latest software developments in the gaming industry, in addition to the already commercially available hardware that is robust and reliable. This allows to overcome VR limitations of the industrial software provided by manufacturing machine producers and it is based on an open-source community programming approach, and also leads to significant advantages such as interfacing with the latest developed hardware for realistic user experience in immersive VR, as well as the possibility to share adaptive algorithms. A practical implementation in Unity is provided as a functional prototype for feasibility tests. However, at the time of this paper, no controlled human-subject studies on the implementation have been noted, in fact, this is solely provided to show preliminary proof of concept. Future work will formally address the questions that are raised in this first run.


165. Review of socio-technical considerations to ensure successful implementation of Industry 4.0

Robert Stephen Davies1, Tim Coole2, Alistair Smith3

1AECOM Ltd, United Kingdom; 2Buckinghamshire New University, High Wycombe, HP11 2JZ, UK; 3Process and Automation Division, AECOM, Manchester, M1 6LT, UK

Industry 4.0 is promoted as the natural continuation of manufacturing evolution and is an amalgamation of technologies made available through the internet, real time communication, advanced analytical capabilities, digital modelling, additive manufacturing and computer integrated manufacturing. This paper proposes the argument that such an amalgamation of technologies will only contribute to the strategic fit for a manufacturing company if the amalgamation is defined within an ‘architecture’ that aligns the capabilities of the company to the needs of their current and potentially emerging customers.

Historically successful manufacturing has exhibited a connection to the customer base by efficiently and economically supplying both the necessary and desirable products that deliver consumer value. Such manufacturers have an infrastructure that matches their capabilities to the needs of their customer base. The success, for example, of manufactures adopting lean systems of production is due to the structural focus of lean to delivering customer value. The Toyota Production System (TPS) evolved through a process of trial and error. Once the ad-hoc progression of the TPS had been conceptualised into a delivery structure that enabled a manufacturer to focus their capabilities to delivering customer value was the TPS successfully adopted across the wider manufacturing landscape and later to both commercial and service sectors. A similar argument can be applied to the Six Sigma approach to continuous improvement. It is the structure and disciplined dissemination of the Six Sigma methodology that leads to successful improvement projects.

It is clear from consulting the general manufacturing and academic literature that the Industry 4.0 model has the potential to leverage manufacturing capability to deliver a more focussed, bespoke and customised delivery of value to an increasingly demanding (and potentially globally expanding) customer base. Currently, Industry 4.0 far many manufactures is shrouded in mystery and what can be confused as jargon (‘The Internet of Things’, ‘Big Data’, ‘Cyber-physical systems’ ….). Consequently, this paper advocates that the successful adoption of Industry 4.0 is best served if the model is framed within a delivery structure or architecture that aligns and promotes the manufacturers capabilities to the requirements of their customer base.

The contribution of this paper to the increasing Industry 4.0 body of knowledge is to propose an alignment architecture that enables manufacturers to leverage their capabilities to ensure a strategic fit to their customer base through the adoption of Industry 4.0 technologies. The paper introduces the Industry 4.0 model and provides definitions to the main 4.0 concepts. The historical evolution of manufacturing is reviewed from a perspective that Industry 4.0 adoption benefits from understanding both the successful and less successful implementations of previous advances in technology and operations management. Based on this approach, the Industry 4.0 architecture is presented followed by concluding remarks.


172. Supporting remote maintenance in industry 4.0 through augmented reality

Riccardo Masoni1, Francesco Ferrise2, Monica Bordegoni2, Michele Gattullo3, Antonio Emmanuele Uva3, Michele Fiorentino3, Ernesto Carrabba4, Michele Di Donato5

1Politecnico di Milano, School of Industrial and Information Engineering, Piazza Leonardo da Vinci, 32, 20133, Milano, Italy; 2Politecnico di Milano, Department of Mechanical Engineering, Via La Masa 1, 20156, Milano, Italy; 3Politecnico di Bari, Department of Mechanics, Mathematics and Management, Viale Japigia 182, 70126, Bari, Italy; 4SITAEL S.p.A, Via San Sabino 21, 70042, Mola di Bari (BA), Italy; 5Amec Foster Wheeler, Via S. Caboto 15, 20094, Corsico (MI), Italy

Due to the Industry 4.0 initiative, AR has started to be considered one of the most interesting technologies companies should invest in, especially in order to improve their maintenance services. Several technological limitations have prevented augmented reality to become an effective industrial tool. In this paper, we critically analyzed the limitations of AR technologies and how they have been overcome in years. We present a novel solution for remote maintenance based on off-the-shelf mobile and AR technologies. The architecture of the application allows us to remotely connecting a skilled operator in a control room with an unskilled one located where the maintenance has to be performed. We describe the important features we have added to its previous version and the rationale behind them in order to make the technical communication more effective.


367. The Challenge of Introducing AR in Industry - Results of a Participative Process Involving Maintenance Engineers

Fabian Quint1, Frieder Loch1, Patrick Bertram2

1German Research Center for Artificial Intelligence, Trippstadter Str. 122, Kaiserslautern 67663, Germany; 2Technologie-Initiative SmartFactoryKL e.V., Germany

Augmented Reality-based applications are increasingly used for industrial scenarios. However, finding use cases that make good use of the characteristics of AR and are reasonable in terms of its creation effort is not straightforward. Only limited requirements and guidelines for identifying useful AR applications in industry can be found. In this paper findings of a user-centered process conducted within an engineering company as well as the resulting use case, its implementation and user feedback are presented.

 
2:20pm - 4:00pmSES 10.7: INTERCONNESSIONE, MODULARITÀ, DIAGNOSTICA: INDUSTRY 4.0 NELL’ASSISTENZA AL VEICOLO
Aula S (first floor) 
4:00pm - 4:20pmClosing Ceremony
Session Chair: Marcello Pellicciari
Session Chair: Margherita Peruzzini
Aula N (first floor) 
7:15pm - 11:00pmGALA DINNER and Awards Ceremony
A shuttle bus service accompanying to the dinner place is included. Meeting Point:
Largo Garibaldi 15 - Modena, in front of Storchi Theater (see the map on www.faim2017.org), h 7.15 (PM)
Corte di Villa Spalletti 
Date: Friday, 30/Jun/2017
8:30am - 12:00pmIND 4: Industrial tour at IMA
Meeting Point: Largo Garibaldi - Modena 
9:00am - 11:00amIND 2: Industrial tour at PAGANI
Meeting Point: Largo Garibaldi - Modena 
9:00am - 12:30pmIND 1.1: Vinegar factory tour (included in LAMBORGHINI tour)
Meeting Point: Largo Garibaldi - Modena 
9:30am - 1:00pmIND 3: Industrial tour at DUCATI
Meeting Point: Largo Garibaldi - Modena 
1:30pm - 4:00pmIND 1.2: Industrial tour at LAMBORGHINI
Meeting Point: Largo Garibaldi - Modena 

 
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