Patrick Eschemann, Philipp Borchers, Linda Feeken, Ingo Stierand, Jan Stefan Zernickel, Martin Neumann
Modelling and Simulation'2020
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.