A model-based Digital Twin to support responsive manufacturing systems

Manufacturing systems are subject to continuous changing conditions, which are due both to external reasons (e.g. changing demand) and to the natural system evolution, (e.g. machine degradation, operators' upskilling). At tactical level, production engineers are challenged to continuously improve the system performance. At strategical level, the manufacturing company must monitor the system status and proactively identify reconfiguration actions to ensure system fitness to the evolving competitive scenario. A novel Digital Twin based on an analytical model for performance evaluation of manufacturing system embedding evaluation of joint parameter variations is introduced. In particular this work concentrates on how tactical decision makers can benefit from an integrated system model. The method is proved in a real industrial case in the railway sector. 0 2021 CIRP. Published by Elsevier Ltd. All rights reserved.

Automated summary

Manufacturing systems are influenced by continuous changing conditions, requiring production engineers to improve system performance and companies to monitor and adapt to evolving competitive environments. This study introduces a novel Digital Twin based on an analytical model for evaluating manufacturing system performance.