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Self-optimizing digital factory twin: an industrial use case

Published online by Cambridge University Press:  16 May 2024

Christian Nigischer ,
Florian Reiterer ,
Sébastien Bougain  and
Manfred Grafinger
Christian Nigischer*
Affiliation:
Austrian Center for Digital Production, Austria
Florian Reiterer
Affiliation:
Nemak Linz GmbH, Austria
Sébastien Bougain
Affiliation:
Austrian Center for Digital Production, Austria
Manfred Grafinger
Affiliation:
TU Wien, Austria
*
christian.nigischer@acdp.at

Abstract

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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.

Keywords

digital twindiscrete-event simulationself-optimising systemsindustrial use case
Type
Artificial Intelligence and Data-Driven Design
Information
Proceedings of the Design Society , Volume 4: DESIGN 2024 , May 2024 , pp. 2159 - 2168
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

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