Conference Agenda

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Session Overview
Session
SES 5.4: Digital Product and Process Development
Time:
Wednesday, 28/Jun/2017:
11:20am - 1:00pm

Session Chair: Marco Mandolini
Location: Aula P (first floor)

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Presentations

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



 
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