Digital twin for CNC machine tool: modeling and using strategy

被引:0
|
作者
Weichao Luo
Tianliang Hu
Chengrui Zhang
Yongli Wei
机构
[1] Shandong University,School of Mechanical Engineering
[2] Shandong University,Key Laboratory of High Efficiency and Clean Mechanical Manufacture
[3] Ministry of Education,National Demonstration Center for Experimental Mechanical Engineering Education
[4] Shandong University,undefined
关键词
CNC machine tool (CNCMT); Digital twin (DT); Smart manufacturing;
D O I
暂无
中图分类号
学科分类号
摘要
As a typical manufacturing equipment, CNC machine tool (CNCMT), which is the mother machine of industry, plays an important role in the new trend of smart manufacturing. As the requirement of smart manufacturing, the abilities of its self-sensing, self-prediction and self-maintenance are necessary. In order to make CNCMT become more intelligent, a research about Digital twin (DT) for CNCMT is conducted. In this research, a multi-domain unified modeling method of DT is established, a mapping strategy between physical space and digital space is explored, and an autonomous strategy of DT is proposed. These methods can optimize the running mode, reduce the sudden failure probability and improve the stability of CNCMT. Finally, this paper provides a demonstration of DT model building and using strategy in fault prediction and diagnosis for CNC milling machine tool.
引用
收藏
页码:1129 / 1140
页数:11
相关论文
共 50 条
  • [1] Digital twin for CNC machine tool: modeling and using strategy
    Luo, Weichao
    Hu, Tianliang
    Zhang, Chengrui
    Wei, Yongli
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2019, 10 (03) : 1129 - 1140
  • [2] Digital Twin modeling method for CNC machine tool
    Luo, Weichao
    Hu, Tianliang
    Zhu, Wendan
    Tao, Fei
    2018 IEEE 15TH INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC), 2018,
  • [3] Digital twin modeling technology and intelligent application of CNC machine tool
    Sun X.
    Zhang F.
    Zhou Z.F.
    Wang J.
    Huang Z.
    Xue R.
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2024, 30 (03): : 825 - 836
  • [4] Digital twin-driven fault diagnosis for CNC machine tool
    Ruijuan Xue
    Peisen Zhang
    Zuguang Huang
    Jinjiang Wang
    The International Journal of Advanced Manufacturing Technology, 2024, 131 : 5457 - 5470
  • [5] Digital twin-driven fault diagnosis for CNC machine tool
    Xue, Ruijuan
    Zhang, Peisen
    Huang, Zuguang
    Wang, Jinjiang
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2024, 131 (11): : 5457 - 5470
  • [6] Digital twin technology applicability evaluation method for CNC machine tool
    Wei, Yongli
    Hu, Tianliang
    Wei, Shiyun
    Ma, Songhua
    Wang, Yanqing
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2024, 131 (11): : 5607 - 5623
  • [7] Consistency retention method for CNC machine tool digital twin model
    Wei, Yongli
    Hu, Tianliang
    Zhou, Tingting
    Ye, Yingxin
    Luo, Weichao
    JOURNAL OF MANUFACTURING SYSTEMS, 2021, 58 : 313 - 322
  • [8] Digital twin technology applicability evaluation method for CNC machine tool
    Yongli Wei
    Tianliang Hu
    Shiyun Wei
    Songhua Ma
    Yanqing Wang
    The International Journal of Advanced Manufacturing Technology, 2024, 131 : 5607 - 5623
  • [9] A hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin
    Luo, Weichao
    Hu, Tianliang
    Ye, Yingxin
    Zhang, Chengrui
    Wei, Yongli
    ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2020, 65
  • [10] Digital Twin-Driven Thermal Error Prediction for CNC Machine Tool Spindle
    Lu, Quanbo
    Zhu, Dong
    Wang, Meng
    Li, Mei
    LUBRICANTS, 2023, 11 (05)