Journal of Computing and Information Science in Engineering · 2022 · 18 citations · 25 references
ComputingDesignSystems EngineeringErgonomicsHuman-centered DesignHuman-computer InteractionComputer-supported Cooperative WorkDigital Twin DesignHuman-cyber-physical InteractionHuman-machine InteractionVirtual TeamworkActivitiesDigital Twin IntegrationDigital Twin InteroperabilityDigital Twin System DesignDigital TwinsPersonal Development MotivationTwinningWork Performance Measurement
Abstract Digital twin (DT) emerges as a key concept of the Industry 4.0 paradigm and beyond. However, the current literature lacks focus on humans and human activities as a part of complex system DTs. Acknowledging human aspects in DTs can enhance work performance, well-being, motivation, and personal development of professionals. This study examines emerging requirements for human digital twins (HDTs) in three use cases of industry–academia collaboration on complex systems. The results draw together the overall design problem and four design objectives for HDTs. We propose to combine the machine and human-related aspects of DTs and highlight the need for virtual-to-virtual interoperability between HDTs and machines alike. Furthermore, we outline differences between humans and machines regarding digital twinning by addressing human activities and knowledge-based behavior on systems. Design of HDTs requires understanding of individual professional characteristics, such as skills and information preferences, together with twinning between the physical and digital machine entities and interactions between the human and machine DTs. As the field moves toward including humans as a part of the DT concept, incorporating HDTs in complex systems emerges as an increasingly significant issue.
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Digital Twin in Industry: State-of-the-Art
Fei Tao, He Zhang, Ang Liu et al. · IEEE Transactions on Industrial Informatics · 2019 · 3.8K citations
Engineering, Industrial Engineering, Manufacturing Engineering +17
Digital Twin: Enabling Technologies, Challenges and Open Research
Aidan Fuller, Zhong Fan, Charles Day et al. · IEEE Access · 2020 · 2.5K citations · Full text
Engineering, Manufacturing Engineering, Artificial Intelligence +14