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STREAM-0D SIGNED

Simulation in Real Time for Manufacturing with Zero Defects

Total Cost €

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EC-Contrib. €

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Partnership

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Project "STREAM-0D" data sheet

The following table provides information about the project.

Coordinator
INSTITUTO TECNOLOGICO DE ARAGON 

Organization address
address: MARIA DE LUNA 8
city: ZARAGOZA
postcode: 50018
website: www.ita.es

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website http://www.stream-0d.eu
 Total cost 5˙063˙828 €
 EC max contribution 4˙159˙145 € (82%)
 Programme 1. H2020-EU.2.1.5.1. (Technologies for Factories of the Future)
 Code Call H2020-FOF-2016
 Funding Scheme IA
 Starting year 2016
 Duration (year-month-day) from 2016-10-01   to  2020-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUTO TECNOLOGICO DE ARAGON ES (ZARAGOZA) coordinator 962˙769.00
2    PANEPISTIMIO PATRON EL (RIO PATRAS) participant 581˙875.00
3    ECOLE CENTRALE DE NANTES FR (NANTES CEDEX 3) participant 503˙571.00
4    STAM SRL IT (GENOVA GE) participant 458˙500.00
5    INTEGRATED ENVIRONMENTAL SOLUTIONS LIMITED UK (GLASGOW) participant 373˙100.00
6    CENTER FOR TECHNOLOGY RESEARCH ANDINNOVATION (CETRI) LTD CY (Nicosia) participant 342˙125.00
7    LUCAS VARITY GMBH DE (KOBLENZ) participant 309˙531.00
8    STANDARD PROFIL SPAIN SA ES (LOGRONO) participant 236˙110.00
9    FERSA BEARINGS, SA ES (ZARAGOZA) participant 212˙187.00
10    DAY ONE SRL IT (ROME) participant 179˙375.00
11    STAMTECH SRL IT (GENOVA) participant 0.00

Map

 Project objective

Facts: i) Zero-defect manufacturing and flexibility of production processes are some of the main challenges for European manufacturing; ii) One of the engineering tools with higher potential is the linking of simulation tools with measurement devices for real-time control of applications. The huge potential of this synergistic loop remains untapped for manufacturing processes and could be used for reducing product variability, increase line flexibility and achieve zero defect production. These objectives could be reached by integrating in the production line multi-physics simulation models, able to predict the product quality indicators in response to the values of critical input parameters (components dimensions, material properties, etc), which are unavoidably subject to variability: different batches, different suppliers,... The models will be fed with actual data from online measurements and, based on the model prediction, the critical steps of the line will be controlled to adjust the product to the exact design specifications or to quickly change specifications for producing customised batches. However, doing this in real time is not possible due to the computational cost of models. Reduced Order Modelling is a new generation of techniques which allow us to obtain parametric solutions of complex models that can be particularized in real time for any value of the parameters. The models run so fast that they can be executed on tablets or smart phones. ROM will be used to transform complex models into the real-time capable models that can be integrated in the production line. Moreover, the online deployment of ROMs and data gathering systems will generate big data which will be exploited through data analysis techniques for further improving the process. The project will show proof-of-concept demonstrations in three real process chains of the automotive sector, covering different types of production methods, products, materials and manufacturing processes.

 Deliverables

List of deliverables.
Public dissemination materials Websites, patent fillings, videos etc. 2020-03-23 11:28:03
Marketing & Dissemination plan Documents, reports 2020-03-23 11:28:03
Project Webpage Websites, patent fillings, videos etc. 2020-03-23 11:28:03

Take a look to the deliverables list in detail:  detailed list of STREAM-0D deliverables.

 Publications

year authors and title journal last update
List of publications.
2019 Domenico Borzacchiello, José V. Aguado, Francisco Chinesta
Non-intrusive Sparse Subspace Learning for Parametrized Problems
published pages: 303-326, ISSN: 1134-3060, DOI: 10.1007/s11831-017-9241-4
Archives of Computational Methods in Engineering 26/2 2020-03-23
2019 Alexios Papacharalampopoulos, Demetris Petrides, Panagiotis Stavropoulos
A defect tracking tool framework for multi-process products
published pages: 523-527, ISSN: 2212-8271, DOI: 10.1016/j.procir.2019.02.100
Procedia CIRP 79 2020-03-23
2018 P. Stavropoulos, H. Alexopoulos, A. Papacharalampopoulos, D. Mourtzis
Automotive weather strip manufacturing: Process modeling and extrudate dimensional accuracy evaluation
published pages: 375-380, ISSN: 2212-8271, DOI: 10.1016/j.procir.2018.03.120
Procedia CIRP 72 2020-03-23

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The information about "STREAM-0D" are provided by the European Opendata Portal: CORDIS opendata.

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