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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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期刊全稱Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Co
期刊簡稱43rd IFIP WG 5.7 Int
影響因子2023Matthias Thürer,Ralph Riedel,David Romero
視頻videohttp://file.papertrans.cn/168/167305/167305.mp4
學(xué)科分類IFIP Advances in Information and Communication Technology
圖書封面Titlebook: Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Co; 43rd IFIP WG 5.7 Int Matthias Thürer,
影響因子.The six-volume set IFIP AICT 728-729 constitutes the refereed proceedings of the 43rd IFIP WG 5.7 International Conference on?Advances in Production Management 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 addressing the overall topic of the conference “Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments”...Part I: advancing eco-efficient and circular industrial practices; barriers and challenges for transition towards circular and sustainable production processes and servitized business models; implementing the EU green deal: challenges and solutions for a sustainable supply chain; risk analysis and sustainability in an uncertain system in a digital era...Part II: smart and sustainable supply chain management in the society 5.0 era; human-centred manufacturing and logistics systems design and management for the operator 5.0; inclusive work systems design: applying technology to accommodate individual workers’
Pindex Conference proceedings 2024
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https://doi.org/10.1007/978-3-663-02551-1hysical 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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https://doi.org/10.1007/978-3-663-02551-1vities in manufacturing systems at various levels of abstraction. In this study, we propose data-driven modeling and scheduling for cellular manufacturing systems using process mining with Petri nets. In the proposed method, the event log data is extracted from a virtual plant and then the Petri net
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https://doi.org/10.1007/978-3-663-02551-1n which packages are placed with the aim of reducing transportation costs and improving productivity. From the viewpoint of actual optimization of the entire factory, it is necessary to consider the motion planning of a robot manipulator to handle the items in the three-dimensional bin packing probl
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https://doi.org/10.1007/978-3-663-02551-1elopment. Moreover, AI can potentially improve decision-making in healthcare supply chains (HSCs) by leveraging the information provided by various sources. However, research on the application of AI to HSCs is still in its infancy. This work presents a Systematic Literature Review to identify the m
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Klimaschutzgesetz und Klimapaket,t should give them. Therefore, organizations should consider these factors in their operational processes. In today’s world, which is mixed with transformative technologies and business and supply chain processes have different conditions than in the past, understanding the CSFs for smart processes
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