Publication | Open Access
Human–Cyber–Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing
457
Citations
81
References
2019
Year
Human–cyber–physical systems (HCPSs) integrate humans, cyber, and physical components to enable intelligent manufacturing, evolving from digital manufacturing to new‑generation intelligent manufacturing (NGIM) driven by AI and advanced manufacturing technologies. This study reviews the evolution of intelligent manufacturing through the HCPS lens, discusses HCPS implications, characteristics, technical framework, and key technologies for NGIM, and outlines major challenges for HCPSs in NGIM. The authors analyze HCPSs by examining their evolutionary footprint, technical frame, and key technologies to assess their role in NGIM.
An intelligent manufacturing system is a composite intelligent system comprising humans, cyber systems, and physical systems with the aim of achieving specific manufacturing goals at an optimized level. This kind of intelligent system is called a human–cyber–physical system (HCPS). In terms of technology, HCPSs can both reveal technological principles and form the technological architecture for intelligent manufacturing. It can be concluded that the essence of intelligent manufacturing is to design, construct, and apply HCPSs in various cases and at different levels. With advances in information technology, intelligent manufacturing has passed through the stages of digital manufacturing and digital-networked manufacturing, and is evolving toward new-generation intelligent manufacturing (NGIM). NGIM is characterized by the in-depth integration of new-generation artificial intelligence (AI) technology (i.e., enabling technology) with advanced manufacturing technology (i.e., root technology); it is the core driving force of the new industrial revolution. In this study, the evolutionary footprint of intelligent manufacturing is reviewed from the perspective of HCPSs, and the implications, characteristics, technical frame, and key technologies of HCPSs for NGIM are then discussed in depth. Finally, an outlook of the major challenges of HCPSs for NGIM is proposed.
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