Process Manufacturing Intelligence Empowered by Industrial Metaverse: A Survey

The intelligent goal of process manufacturing is to achieve high efficiency and greening of the entire production. Whereas the information system it used is functionally independent, resulting to knowledge gaps between each level. Decision-making still requires lots of knowledge workers making manua...

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Veröffentlicht in:IEEE transactions on cybernetics 2024-11, Vol.54 (11), p.6679-6692
Hauptverfasser: Luo, Weichao, Huang, Keke, Liang, Xiaojun, Ren, Hao, Zhou, Nan, Zhang, Chaobo, Yang, Chunhua, Gui, Weihua
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Sprache:eng
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Zusammenfassung:The intelligent goal of process manufacturing is to achieve high efficiency and greening of the entire production. Whereas the information system it used is functionally independent, resulting to knowledge gaps between each level. Decision-making still requires lots of knowledge workers making manually. The industrial metaverse is a necessary means to bridge the knowledge gaps by sharing and collaborative decision-making. Considering the safety and stability requirements of the process manufacturing, this article conducts a thorough survey on the process manufacturing intelligence empowered by industrial metaverse. First, it analyzes the current status and challenges of process manufacturing intelligence, and then summarizes the latest developments about key enabling technologies of industrial metaverse, such as interconnection technologies, artificial intelligence, cloud-edge computing, digital twin (DT), immersive interaction, and blockchain technology. On this basis, taking into account the characteristics of process manufacturing, a construction approach and architecture for the process industrial metaverse is proposed: a virtual-real fused industrial metaverse construction method that combines DTs with physical avatar, which can effectively ensure the safety of metaverse's application in industrial scenarios. Finally, we conducted preliminary exploration and research, to prove the feasibility of proposed method.
ISSN:2168-2267
2168-2275
2168-2275
DOI:10.1109/TCYB.2024.3420958