Title:
Digital twin driven assembly line re-balancing and decision support
Authors:
- Giovanni Lugaresi
- Kornel Tamas
- Kovacs Laszlo
Published in:
(2024). ECMS 2024, 38th Proceedings
Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2024
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-84-5
ISBN: 978-3-937436-83-8 (CD) Communications of the ECMS Volume 38, Issue 1, June 2024, Cracow, Poland June 4th – June 7th, 2024
DOI:
https://doi.org/10.7148/2024-0164
Citation format:
Giovanni lugaresi, Kornel tamas, Kovacs laszlo (2024). Digital Twin Driven Assembly Line Re-Balancing and Decision Support, ECMS 2024, Proceedings Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation. doi:10.7148/2024-0164
Abstract:
Recent investments in industrial digitization together with the concrete need for short-term planning capabilities mean digital twins can effectively aid enterprises in the management of their production systems and value chains. This paper introduces a conceptual framework for assembly line re-balancing in the context of Industry 5.0, focusing on manual assembly processes. The framework aims to leverage a digital twin for obtaining a synchronized representation of the current task allocations in the assembly line, and uses data-driven scenario generation methods for investigating alternative balancing solutions that are proposed to operators in real time.
A proof-of-concept platform is implemented in a laboratory environment, utilizing an assembly line with industrial components. Preliminary results demonstrate the compatibility of the proposed components within the digital twin framework. The potential applicability to various manual assembly scenarios is discussed, along with considerations for incorporating additional constraints in the evaluation process.
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