Abstract
In rechargeable battery production—a component of mass customization—high quality, low cost, efficient delivery, and flexibility must be ensured. Efficient production operation can be achieved by solving the performance degradation problem, which is a limitation of mass customization. This degradation can be prevented through resilience, which can be achieved by satisfying four core functional requirements, which are as follows: (1) selecting robust actions; (2) measuring performance indicators; (3) notifying impermissible fluctuations; and (4) extracting the adjusted reactions. A digital twin (DT) is an advanced virtual asset that represents configuration, reflects functional units, and synchronizes information objects. This article describes DT application to satisfy the four core functional requirements and reflect the operational characteristics of three heterogeneous stations in rechargeable battery production. Analyses of the measures taken to achieve the resilience and operational characteristics of stations in rechargeable battery production are provided to present an appropriate design of the description. The asset description is designed with P4R classes based on this analysis. The designed asset description is applied to stations in rechargeable battery production, and the proposed method is verified with the implemented DT application. The proposed asset description presents an efficient method of satisfying the core activities and technical functionalities corresponding to the DT. The proposed method is an early case of DT usage in rechargeable battery production and can be considered as a reference for smart manufacturing technologies in the manufacturing domain in the future.
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Funding Acknowledgement
This study was partly supported by the Smart Manufacturing Innovation Technology Development Programs under Grant [2022-0-01024, Development of International Standard-based Digital Twin Management Technology for Large-scale Optimal CPPS Operation] and Grant [2022-0-00131, Development of an AI-based Production Planning Technology for Reconfigurable Manufacturing Systems] funded by Ministry of Science and ICT.
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Park, K.T., Park, Y.H., Choi, YH., Park, MW., Noh, S.D. (2022). Asset Description of Digital Twin for Resilient Production Control in Rechargeable Battery Production. In: Kim, D.Y., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. APMS 2022. IFIP Advances in Information and Communication Technology, vol 664. Springer, Cham. https://doi.org/10.1007/978-3-031-16411-8_62
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