Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing |
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Authors: | Guanghui Zhou Chao Zhang Zhi Li Kai Ding Chuang Wang |
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Affiliation: | 1. School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, People’s Republic of China;2. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, People’s Republic of Chinaghzhou@mail.xjtu.edu.cn;4. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Konghttps://orcid.org/0000-0002-8121-0258;5. Institute of Internet of Things and IT-based Industrialization, Xi’an University of Posts and Telecommunications, Xi’an, People’s Republic of China |
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Abstract: | Rapid advances in new generation information technologies, such as big data analytics, internet of things (IoT), edge computing and artificial intelligence, have nowadays driven traditional manufacturing all the way to intelligent manufacturing. Intelligent manufacturing is characterised by autonomy and self-optimisation, which proposes new demands such as learning and cognitive capacities for manufacturing cell, known as the minimum implementation unit for intelligent manufacturing. Consequently, this paper proposes a general framework for knowledge-driven digital twin manufacturing cell (KDTMC) towards intelligent manufacturing, which could support autonomous manufacturing by an intelligent perceiving, simulating, understanding, predicting, optimising and controlling strategy. Three key enabling technologies including digital twin model, dynamic knowledge bases and knowledge-based intelligent skills for supporting the above strategy are analysed, which equip KDTMC with the capacities of self-thinking, self-decision-making, self-execution and self-improving. The implementing methods of KDTMC are also introduced by a thus constructed test bed. Three application examples about intelligent process planning, intelligent production scheduling and production process analysis and dynamic regulation demonstrate the feasibility of KDTMC, which provides a practical insight into the intelligent manufacturing paradigm. |
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Keywords: | Intelligent manufacturing digital twin dynamic knowledge bases knowledge-based intelligent skills digital twin manufacturing cell |
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