Integrated Zero Defect Manufacturing Solution for High Value Adding Multi-stage Manufacturing systems

Informations projet

ForZDM

N° de convention de subvention: 723698

DOI 10.3030/723698

Projet clôturé

Date de signature de la CE 1 Juillet 2016

Date de début 1 Octobre 2016

Date de fin 31 Mars 2021

Financé au titre de

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing

Coût total € 7 566 108,75

Contribution de l’UE € 5 896 860,40

Coordonné par

POLITECNICO DI MILANO
Italy

Livrables

Other (5)

Heterogeneous data correlation, error budgeting and root cause analysis tool

This deliverable reports results from task 4.1. It includes a document and a product (software)

Critical process models

This deliverable reports results from task 4.2. It includes a document and a product (software)

Product variation models

This deliverable reports results from task 4.3. It includes a document and a product (software)

Integrated quality and logistics process-chain modelling and analysis tool

This deliverable reports results from tasks 5.1, 5.2, 5.3. It includes a document and a product (software)

Sensitivity analysis tool

This deliverable reports results from task 5.4. It includes a document and a product (software)

Demonstrators, pilots, prototypes (3)

Demonstration of use case 3

This deliverable focuses on the implementation of project results in the third demo (task 7.3)

Demonstration of use case 2

This deliverable focuses on the implementation of project results in the second demo (task 7.2)

Demonstration of use case 1

This deliverable focuses on the implementation of project results in the first demo (task 7.1)

Websites, patent fillings, videos etc. (1)

Project website

This deliverable provides a product, a website for internal and external project communication

Documents, reports (2)

ZDM strategy, vision and framework: book and a public white paper

This deliverable generalizes and formalizes the ForZDM approach

Evaluation of KPIs and impacts of the use cases

This deliverable reports results from task 7.4

Publications

Peer reviewed articles (9)

Web-based Platform for Data Analysis and Monitoring

Auteurs: Colin Reiff, Stefan Oechsle, Florian Eger, Alexander Verl
Publié dans: Procedia CIRP, Numéro 86, 2019, Page(s) 31-36, ISSN 2212-8271
Éditeur: CIRP
DOI: 10.1016/j.procir.2020.01.009

Indirect cutting tool wear classification using deep learning and chip colour analysis

Auteurs: Luca Pagani, Paolo Parenti, Salvatore Cataldo, Paul J. Scott, Massimiliano Annoni
Publié dans: The International Journal of Advanced Manufacturing Technology, Numéro 111/3-4, 2020, Page(s) 1099-1114, ISSN 0268-3768
Éditeur: Springer Verlag
DOI: 10.1007/s00170-020-06055-6

Reference architecture for the industrial implementation of Zero-Defect Manufacturing strategies

Auteurs: Maria Chiara Magnanini, Marcello Colledani, Davide Caputo
Publié dans: Procedia CIRP, Numéro 93, 2020, Page(s) 646-651, ISSN 2212-8271
Éditeur: Elsevier
DOI: 10.1016/j.procir.2020.05.154

Reaching Zero-Defect Manufacturing by Compensation of Dimensional Deviations in the Manufacturing of Rotating Hollow Parts

Auteurs: F. Eger, C. Reiff, P. Tempel, M.C. Magnanini, D. Caputo, A. Lechler, A. Verl
Publié dans: Procedia Manufacturing, Numéro 51, 2020, Page(s) 388-393, ISSN 2351-9789
Éditeur: FAIM 2021
DOI: 10.1016/j.promfg.2020.10.055

Smart centering for rotation-symmetric parts in multi-stage production systems for zero-defect manufacturing

Auteurs: Colin Reiff, Florian Eger, Philipp Tempel, Maria Chiara Magnanini, Jon Ander Ortiz, Marcello Colledani, Alexander Verl, Iñigo Sarries
Publié dans: Procedia CIRP, Numéro 79, 2019, Page(s) 27-32, ISSN 2212-8271
Éditeur: Elsevier
DOI: 10.1016/j.procir.2019.02.006

Correlation analysis methods in multi-stage production systems for reaching zero-defect manufacturing

Auteurs: Florian Eger, Colin Reiff, Bernd Brantl, Marcello Colledani, Alexander Verl
Publié dans: Procedia CIRP, Numéro 72, 2018, Page(s) 635-640, ISSN 2212-8271
Éditeur: Elsevier
DOI: 10.1016/j.procir.2018.03.163

Zero Defect Manufacturing Strategies for Reduction of Scrap and Inspection Effort in Multi-stage Production Systems

Auteurs: Florian Eger, Daniel Coupek, Davide Caputo, Marcello Colledani, Mariluz Penalva, Jon Ander Ortiz, Hermann Freiberger, Gernot Kollegger
Publié dans: Procedia CIRP, Numéro 67, 2018, Page(s) 368-373, ISSN 2212-8271
Éditeur: Elsevier
DOI: 10.1016/j.procir.2017.12.228

A control model for downstream compensation strategy in multi-stage manufacturing systems of complex parts

Auteurs: Maria Chiara Magnanini, Florian Eger, Colin Reiff, Marcello Colledani, Alexander Verl
Publié dans: IFAC-PapersOnLine, Numéro 52/13, 2019, Page(s) 1473-1478, ISSN 2405-8963
Éditeur: IFAC
DOI: 10.1016/j.ifacol.2019.11.407

MACHINE LEARNING-BASED ANALYSIS ENGINE TO IDENTIFY CRITICAL VARIABLES IN MULTI-STAGE PROCESSES: APPLICATION TO THE INSTALLATION OF BLIND FASTENERS

Auteurs: MAIALEN MURUA, FERNANDO VEIGA SUAREZ, JUAN ANTONIO ORTEGA LALMOLDA, MARILUZ PENALVA OSCOZ, ALBERTO DIEZ OLIVAN
Publié dans: DYNA, Numéro 95/1, 2020, Page(s) 534-540, ISSN 1989-1490
Éditeur: Dyna Ingenieria e Industria
DOI: 10.6036/9403

Conference proceedings (2)

Part Variation Modeling in Multi-Stage Production Systems for Zero-Defect Manufacturing

Auteurs: Florian Eger, Philipp Tempel, Maria Chiara Magnanini, Colin Reiff, Marcello Colledani, Alexander Verl
Publié dans: 2019 IEEE International Conference on Industrial Technology (ICIT), 2019, Page(s) 1017-1022, ISBN 978-1-5386-6376-9
Éditeur: IEEE
DOI: 10.1109/ICIT.2019.8754964

Knowledge Capturing Platform in Multi-Stage Production Systems for Zero-Defect Manufacturing

Auteurs: Florian Eger, Colin Reiff, Marcello Colledani, Alexander Verl
Publié dans: 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), 2018, Page(s) 1-6, ISBN 978-1-5386-7544-1
Éditeur: IEEE
DOI: 10.1109/M2VIP.2018.8600910