CNC Machine Tool Fault Diagnosis Integrated Rescheduling Approach Supported by Digital Twin-Driven Interaction and Cooperation Framework

被引:13
|
作者
Liu, Jinsong [1 ,2 ]
Yu, Dong [2 ]
Hu, Yi [2 ,3 ]
Yu, Haoyu [1 ,2 ]
He, Wuwei [1 ,2 ]
Zhang, Lipeng [1 ,2 ]
机构
[1] Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China
[2] Chinese Acad Sci, Shenyang Inst Comp Technol, Shenyang 110168, Peoples R China
[3] Shenyang CASNC Technol Co Ltd, Shenyang 110168, Peoples R China
关键词
Fault diagnosis; Production; Digital twin; Real-time systems; Manufacturing; Job shop scheduling; Machine tools; fault diagnosis; knowledge graph; MCTS; rescheduling; NEURAL-NETWORKS; INDUSTRY; 4.0; BIG DATA; SYSTEM;
D O I
10.1109/ACCESS.2021.3106797
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The problems of CNC machine tool (CNCMT) fault diagnosis and production rescheduling have attracted continuous attention because of their great significance to the manufacturing industry. Digital twin is a supporting technology for achieving smart manufacturing and provides a new paradigm for solving these problems. This paper explores a digital twin-driven interaction and cooperation framework and proposes the architecture and implementation mechanism to enable the sharing of data, knowledge, and resource, to realize the fusion of physical space and cyber space, and to improve the accuracy of fault diagnosis. Under this framework, aiming at the influence of CNCMT failure on the initial production planning, a self-adaptation rescheduling method based on Monte Carlo Tree Search (MCTS) algorithm is proposed to provide support for developing more efficient production planning. Finally, the effectiveness of the proposed framework is validated by experimental study. The framework and integrated rescheduling approach can provide guidance for enterprises in implementing CNCMT maintenance and production scheduling to meet high accuracy and reliability requirements.
引用
收藏
页码:118801 / 118814
页数:14
相关论文
共 31 条
  • [1] 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
  • [2] 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
  • [3] Digital Twin-Driven Thermal Error Prediction for CNC Machine Tool Spindle
    Lu, Quanbo
    Zhu, Dong
    Wang, Meng
    Li, Mei
    LUBRICANTS, 2023, 11 (05)
  • [4] A digital twin-driven hybrid approach for the prediction of performance degradation in transmission unit of CNC machine tool
    Yang, Xin
    Ran, Yan
    Zhang, Genbao
    Wang, Hongwei
    Mu, Zongyi
    Zhi, Shengguang
    ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2022, 73
  • [5] Digital twin-driven virtual commissioning of machine tool
    Wang, Jinjiang
    Niu, Xiaotong
    Gao, Robert X.
    Huang, Zuguang
    Xue, Ruijuan
    ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2023, 81
  • [6] A digital twin-driven approach for partial domain fault diagnosis of rotating machinery
    Xia, Jingyan
    Chen, Zhuyun
    Chen, Jiaxian
    He, Guolin
    Huang, Ruyi
    Li, Weihua
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2024, 131
  • [7] A digital twin-driven approach for partial domain fault diagnosis of rotating machinery
    Xia, Jingyan
    Chen, Zhuyun
    Chen, Jiaxian
    He, Guolin
    Huang, Ruyi
    Li, Weihua
    Engineering Applications of Artificial Intelligence, 2024, 131
  • [8] Digital Twin-Driven Fault Diagnosis for Autonomous Surface Vehicles
    Bhagavathi, Ravitej
    Kufoalor, D. Kwame Minde
    Hasan, Agus
    IEEE ACCESS, 2023, 11 : 41096 - 41104
  • [9] Digital twin-driven intelligent fault diagnosis technology for crushers
    Gao, Pubo
    Ma, Aixiang
    Yan, Xihao
    Chu, Xu
    Liu, Xiuyun
    Zhao, Sihai
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2025, 36 (04)
  • [10] 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