Titlebook: Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Co; 43rd IFIP WG 5.7 Int Matthias Thürer,

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Conference proceedings 2024Management Systems, APMS 2024, held in Chemnitz, Germany, during?September 8–12, 2024...The 201 full papers presented together were carefully reviewed and selected from 224 submissions.?The APMS 2024 conference proceedings are organized into six volumes, covering a large spectrum of research address

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Data-Driven Control System Using Machine Learning in Production Processhysical or chemical models. Those models are developed from knowledge of the physical or chemical changes that occur when the products are processed and operational knowledge. However, it is difficult for some companies to research physical or chemical models. We study data-driven control systems to

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Trading Digital-Valued Assets Within Cyber-Physical Manufacturing Supply Chains: A Scoping Review ofital assets globally, additive manufacturing can support Industry 5.0 principles like sustainability or resilience. Thus, examining the potential for digital trade within cyber-physical manufacturing supply chains is crucial. This paper responds to the research challenge by providing an overview of

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Basic Research on Laborer State Prediction Towards the Realization of Human Digital Twinly difficult to achieve the conventional uniformity of machine-centered production, the ability to respond to diverse needs, and the improvement of production efficiency. In addition, Japan will become a super-aging society where 40% of the population will be elderly by 2060, and there is an urgent

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Resilient Supply Chain Network Planning Method with Two-Stage Stochastic Programming: Extension to Mign resilient supply chains that can maintain production capacity by preparing for and responding to predictable risks. Our group has proposed strategic planning methodologies for the selection of appropriate material suppliers and the optimization of inventory levels across the supply chain, includ