Nigischer, C., Reiterer, F., Bougain, S., & Grafinger, M. (2024). Self-optimizing digital factory twin: an industrial use case. In Proceedings of the Design Society (pp. 2159–2168). Cambridge University Press. https://doi.org/10.1017/pds.2024.218
E307-04 - Forschungsbereich Maschinenbauinformatik und Virtuelle Produktentwicklung E307-02-1 - Forschungsgruppe Maschinenelemente und Luftfahrtgetriebe E349-02 - Fachbereich CAD/PC-Labor
-
Published in:
Proceedings of the Design Society
-
Volume:
4
-
Date (published):
16-May-2024
-
Event name:
2024 International Design Society Conference, Design 2024
en
Event date:
20-May-2024 - 23-May-2024
-
Event place:
Cavtat, Croatia
-
Number of Pages:
10
-
Publisher:
Cambridge University Press
-
Peer reviewed:
Yes
-
Keywords:
digital twin; discrete-event simulation; industrial use case; self-optimising systems
en
Abstract:
Digital Twins (DTs) are intended to be utilized for a wide range of applications, promising benefits like visualization, monitoring, simulation and control of a physical system. Not only the development of a DT for a production facility is a time-consuming task, but also to keep the virtual counterpart up to date in the use phase. In this work, the implementation of an industrial-scale DT of an automotive supplier production site based on a Discrete-Event Simulation (DES) model with self-optimization capabilities for easier maintainability and increased simulation accuracy is presented.
