Conference Agenda

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Session Overview
SES 9.1: Robots in AVM
Thursday, 29/Jun/2017:
11:20am - 1:00pm

Session Chair: Rezia Molfino
Location: Aula Convegni (first floor)

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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.

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