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Toward Intelligent Machine Tool

delete2019-08-01
delete58
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OA
AI
J
Jihong Chen
胡
胡鹏程 (Pengcheng Hu)
周惠成 封面图
周惠成 (Huicheng Zhou)
J
Jianzhong Yang *
J
Jiejun Xie
Y
Yakun Jiang
Z
Zhiqiang Gao
C
Chenglei Zhang
DOI:10.1016/j.eng.2019.07.018delete
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摘要

摘要

En 中文
With the development of modern information technology-and particularly of the new generation of artificial intelligence (AI) technology-new opportunities are available for the development of the intelligent machine tool (IMT). Based on the three classical paradigms of intelligent manufacturing as defined by the Chinese Academy of Engineering, the concept, characteristics, and systemic structure of the IMT are presented in this paper. Three stages of machine tool evolution-from the manually operated machine tool (MOMT) to the IMT-are discussed, including the numerical control machine tool (NCMT), the smart machine tool (SMT), and the IMT. Furthermore, the four intelligent control principles of the IMT-namely, autonomous sensing and connection, autonomous learning and modeling, autonomous optimization and decision-making, and autonomous control and execution-are presented in detail. This paper then points out that the essential characteristic of the IMT is to acquire and accumulate knowledge through learning, and presents original key enabling technologies, including the instruction-domain-based analytical approach, theoretical and big-data-based hybrid modeling technology, and the double-code control method. Based on this research, an intelligent numerical control (INC) system and industrial prototypes of IMTs are developed. Three intelligent practices are conducted, demonstrating that the integration of the new generation of AI technology with advanced manufacturing technology is a feasible and convenient way to advance machine tools toward the IMT. (C) 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.
Keyword:
Intelligent manufacturing
Intelligent machine tool
Intelligent numerical controller
New-generation artificial intelligence
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Engineering 封面图
Engineering
IF:
11.6
论文数:
2.7K
被引数:
1.5W

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