Digital twin-driven intelligent production line for automotive MEMS pressure sensors

被引:12
|
作者
Zhang, Quanyong [1 ]
Shen, Shengnan [2 ]
Li, Hui [1 ,2 ,6 ]
Cao, Wan [3 ]
Tang, Wen [3 ]
Jiang, Jing [4 ]
Deng, Mingxing [5 ]
Zhang, Yunfan [1 ]
Gu, Beikang [2 ]
Wu, Kangkang [2 ]
Zhang, Kun [5 ]
Liu, Sheng [1 ,2 ,6 ]
机构
[1] Wuhan Univ, Inst Technol Sci, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Sch Power & Mech Engn, Wuhan 430072, Peoples R China
[3] Wuhan FineMEMS Inc, Wuhan 430075, Peoples R China
[4] Wuhan Huagong Cyber Data Syst Co Ltd, Wuhan 430074, Peoples R China
[5] Wuhan Univ Sci & Technol, Sch Automobile & Traff Engn, Wuhan 430065, Peoples R China
[6] Wuhan Univ, Inst Technol Sci, Sch Power & Mech Engn, Wuhan 430072, Peoples R China
关键词
Digital twin; Multi -source heterogeneous data acquisition; Parallel control; Real-time monitoring and mapping; Process optimization; SHOP-FLOOR; DESIGN;
D O I
10.1016/j.aei.2022.101779
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The equipment and technological processes used in manufacturing electronic products are gradually being automated and networked. Currently, digital twin technology continues to evolve and mature. The electronics manufacturing industry is undergoing an intelligent and digital transformation. Micro-electro-mechanical system (MEMS) sensors have been widely used in the automotive field due to their small size, low cost, and high reli-ability. In this study, a new intelligent production line for automotive MEMS pressure sensors driven by digital twin is individually designed. The intelligent production line system consists of physical production lines, digital production lines, twin data, and data service systems. The technology of multi-source heterogeneous data acquisition is used to process and analyze data collected in real time in a physical production line. Based on the technology of parallel control, the physical and digital production lines are synchronized. To obtain optimal process parameters, a process database is established through the analysis of the key processes of the production line. Three types of automotive MEMS pressure sensors are successfully manufactured in the constructed digital twin-driven intelligent production line. The intelligent production line can realize 24-h unattended operation. The product yield is above 98 %, and the takt time is less than 16 s.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Digital twin-driven intelligent production line for automotive MEMS pressure sensors
    Zhang, Quanyong
    Shen, Shengnan
    Li, Hui
    Cao, Wan
    Tang, Wen
    Jiang, Jing
    Deng, Mingxing
    Zhang, Yunfan
    Gu, Beikang
    Wu, Kangkang
    Zhang, Kun
    Liu, Sheng
    Advanced Engineering Informatics, 2022, 54
  • [2] Application Research of Digital Twin-Driven Ship Intelligent Manufacturing System: Pipe Machining Production Line
    Wu, Qingcai
    Mao, Yunsheng
    Chen, Jianxun
    Wang, Chong
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (03)
  • [3] Digital twin-driven intelligent construction: Features and trends
    Zhang H.
    Zhou Y.
    Zhu H.
    Sumarac D.
    Cao M.
    SDHM Structural Durability and Health Monitoring, 2021, 15 (03): : 183 - 206
  • [4] A digital twin-driven production management system for production workshop
    Ma, Jun
    Chen, Huimin
    Zhang, Yu
    Guo, Hongfei
    Ren, Yaping
    Mo, Rong
    Liu, Luyang
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2020, 110 (5-6): : 1385 - 1397
  • [5] Digital twin-driven intelligent assessment of gear surface degradation
    Feng, Ke
    Ji, J. C.
    Zhang, Yongchao
    Ni, Qing
    Liu, Zheng
    Beer, Michael
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 186
  • [6] A digital twin-driven production management system for production workshop
    Jun Ma
    Huimin Chen
    Yu Zhang
    Hongfei Guo
    Yaping Ren
    Rong Mo
    Luyang Liu
    The International Journal of Advanced Manufacturing Technology, 2020, 110 : 1385 - 1397
  • [7] Multi-objective optimization of the mixed-flow intelligent production line for automotive MEMS pressure sensors
    Quanyong Zhang
    Hui Li
    Shengnan Shen
    Wan Cao
    Jing Jiang
    Wen Tang
    Yuanshun Hu
    Applied Intelligence, 2025, 55 (1)
  • [8] Digital twin-driven online intelligent assessment of wind turbine gearbox
    Zhou, Yadong
    Zhou, Jianxing
    Cui, Quanwei
    Wen, Jianmin
    Fei, Xiang
    WIND ENERGY, 2024, 27 (08) : 797 - 815
  • [9] Digital twin-driven intelligent assembly method for high precision products
    Sun X.
    Liu S.
    Shen X.
    Huang D.
    Bao J.
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2022, 28 (06): : 1704 - 1716
  • [10] Digital twin-driven aero-engine intelligent predictive maintenance
    Xiong, Minglan
    Wang, Huawei
    Fu, Qiang
    Xu, Yi
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2021, 114 (11-12): : 3751 - 3761