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Engineering    2018, Vol. 4 Issue (1) : 11 -20
Research |
Toward New-Generation Intelligent Manufacturing
Zhou Ji1,Li Peigen2,Zhou Yanhong2(),Wang Baicun3(),Zang Jiyuan3,Meng Liu3
1. Chinese Academy of Engineering, Beijing 100088, China
2. Huazhong University of Science and Technology, Wuhan 430074, China
3. Tsinghua University, Beijing 100084, China

Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and newgeneration intelligent manufacturing. New-generation intelligent manufacturing represents an indepth integration of new-generation artificial intelligence (AI) technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs) reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for ‘‘parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China.

Keywords Advanced manufacturing      New-generation intelligent manufacturing      Human-cyber-physical system      New-generation AI      Basic paradigms      Parallel promotion      Integrated development     
Corresponding Authors: Zhou Yanhong,Wang Baicun   
Just Accepted Date: 08 February 2018   Issue Date: 10 April 2018
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Zhou Ji
Li Peigen
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Wang Baicun
Zang Jiyuan
Meng Liu
Cite this article:   
Zhou Ji,Li Peigen,Zhou Yanhong, et al. Toward New-Generation Intelligent Manufacturing[J]. Engineering, 2018, 4(1): 11 -20 .
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