Towards Digital Twins for Optimizing the Factory of the Future


Logistics are essential regarding the efficiency of factories, and therefore their optimization increases productivity. This paper presents an approach and an initial implementation for optimizing a fleet of automated transport vehicles, which transports products between machines in the factory of the future. The approach exploits a digital twin derived from a model of the factory representing the artifacts and information flow required to build a valid digital twin. It can be executed faster than real-time in order to assess different configurations, before the best-fitting choice is applied to the real factory. The paper also gives an outlook on how the digital twin will be extended in order to use it for additional optimization aspects and to improve resilience of the transport fleet against anomalies.

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Patrick Eschemann, Phillip Borchers, Linda Feeken, Ingo Stierand, Jan Zernickel & Martin Neumann

A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future


In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.

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Adrien Bécue (AIRBUS CyberSecurity), Eva Maia (School of Engineering, Polytechnic of Porto (ISEP/IPP)/GECAD)), Linda Feeken (OFFIS e.V.-Institut für Informatik), Philipp Borchers (OFFIS e.V.-Institut für Informatik), Isabel Praça (School of Engineering, Polytechnic of Porto (ISEP/IPP)/GECAD))
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Bécue, A.; Maia, E.; Feeken, L.; Borchers, P.; Praça, I. A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future. Appl. Sci. 202010, 4482.