Abstract
The value-driven Industry 5.0 has brought a shift in the approach towards worker well-being. However, the understanding of the effects on workers due to technological advancements of Industry 4.0, based on a human-centric approach, is limited. The reason for this limitation is that the tools are scarce, which is quantitatively evaluating and analyzing various factors in the workplace. To solve this problem, we propose a human digital twin system supporting decision-making regarding safety management and work management of workers. The human digital twin system consists of a digital twin module, an analysis module, and a visualization module. The proposed system connects a physical human and a virtual digital human model; analyzes the location, posture, and motion-time of workers; and delivers information about safety and work management. This information enables workers and managers to improve the work environment by making them resilient to workplace factors.
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Acknowledgement
This research was financially supported by the MOTIE and KIAT through the Inter-national Cooperative R&D program [P0009839] and supported by project for Smart Manufacturing Innovation R&D funded Korea Ministry of SMEs and Startups in 2022 [RS-2022–00140261].
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Kim, GY. et al. (2022). Human Digital Twin System for Operator Safety and Work Management. 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_61
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DOI: https://doi.org/10.1007/978-3-031-16411-8_61
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