Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing
文献类型:期刊论文
作者 | Jing Yang1,8; Yutong Wang1![]() ![]() ![]() |
刊名 | IEEE Transactions on Systems, Man, and Cybernetics: Systems
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出版日期 | 2024-01 |
页码 | 1-15 |
英文摘要 | Since Manufacturing 4.0 faces various challenges, including the risks of data leakage and privacy violation, the struggle to meet the growing demand for personalization, and the limitations in harnessing human creativity, it has become crucial to embark on a transformation toward Manufacturing 5.0. To this end, we propose a DeFACT framework for parallel manufacturing and Manufacturing 5.0, which focuses on safe, efficient and personalized collaborative production. In DeFACT, different enterprises and parallel workers (i.e., digital, robotic and biological workers) are organized, coordinated and scheduled based on decentralized autonomous organizations and operations to promote mutual benefits among members, even in the context of low or zero trust. This contributes to providing customers with higher-quality personalized products and services while ensuring the confidentiality and safeguarding of data. Additionally, various advanced technologies, such as generative artificial intelligence, scenarios engineering, and blockchain, are leveraged to achieve trustworthy and adaptable decision making, user-friendly human–machine interaction, and the federated control and management of parallel workers. Finally, the effectiveness and efficiency of DeFACT are experimentally validated through the design and implementation of three case studies. |
源URL | [http://ir.ia.ac.cn/handle/173211/57289] ![]() |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
通讯作者 | Yutong Wang |
作者单位 | 1.the State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences 2.the State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences 3.the School of Artificial Intelligence, University of Chinese Academy of Sciences 4.Beijing Engineering Research Center of Intelligent Systems and Technology, Chinese Academy of Sciences 5.the Macau University of Science and Technology 6.the School of Artificial Intelligence, Anhui University 7.Beijing SANBODY Technology Company Ltd. 8.the School of Artificial Intelligence, University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Jing Yang,Yutong Wang,Xingxia Wang,et al. Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems,2024:1-15. |
APA | Jing Yang,Yutong Wang,Xingxia Wang,Xiaoxing Wang,Xiao Wang,&Fei-Yue Wang.(2024).Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing.IEEE Transactions on Systems, Man, and Cybernetics: Systems,1-15. |
MLA | Jing Yang,et al."Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing".IEEE Transactions on Systems, Man, and Cybernetics: Systems (2024):1-15. |
入库方式: OAI收割
来源:自动化研究所
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