Digital twin driven intelligent manufacturing for FPCB etching production line

被引:3
|
作者
Sheng, Jiazheng [1 ]
Zhang, Quanyong [2 ]
Li, Hui [1 ,2 ,3 ,4 ]
Shen, Shengnan [1 ,2 ]
Ming, Ruijian [1 ]
Jiang, Jing [5 ]
Li, Qing [5 ]
Su, Guoxiong [5 ]
Sun, Bin [6 ]
Wang, Jian [6 ]
Yang, Jie [6 ]
Huang, Chunsheng [6 ]
机构
[1] Wuhan Univ, Sch Power & Mech Engn, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Inst Technol Sci, Wuhan 430072, Peoples R China
[3] Wuhan Univ, Hubei Prov Engn Res Ctr Integrated Circuit Packagi, Wuhan 430072, Peoples R China
[4] Wuhan Univ, Hubei Key Lab Elect Mfg & Packaging Integrat, Wuhan 430072, Peoples R China
[5] Wuhan Hgcyber Data Syst Co Ltd, Wuhan 430223, Peoples R China
[6] Jiangsu Leader Tech Semicond Co Ltd, Pizhou 221300, Peoples R China
关键词
Digital twin; FPCB; Intelligent manufacturing; Real time mapping and online control; Product yield; SIMULATION; DESIGN;
D O I
10.1016/j.cie.2023.109763
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Flexible printed circuit board (FPCB) exhibits high wiring density and good bendability to be widely used in smart devices. Traditional FPCB etching production lines are mostly discrete manufacturing workshops, which need to be upgraded with intelligence to meet the production requirements of high precision, production efficiency, and product yield. As an emerging technology, the digital twin can achieve the interoperability between physical and digital worlds of manufacturing systems. In this study, a digital twin driven FPCB etching intelligent production line is design. Data service system obtains comprehensive data from the production line in real time and provides intelligent data services. Real time mapping and online control system accomplishes the real time mapping and closed-loop control of intelligent production line. Key process databases are established to obtain optimal process parameters by analyzing the key processes of FPCB etching intelligent production line. The result shows that the process parameters of production line can be updated and adjusted accurately in real time to ensure good consistency and reliability of products. Currently, the FPCB etching intelligent production line can achieve the line forming at the minimum 16 mu m line pitch and significantly improve the product yield.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Application Research of Digital Twin-Driven Ship Intelligent Manufacturing System: Pipe Machining Production Line
    Wu, Qingcai
    Mao, Yunsheng
    Chen, Jianxun
    Wang, Chong
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (03)
  • [2] Research on Intelligent Manufacturing Flexible Production Line System based on Digital Twin
    Qi Yu-ming
    Xie Bing
    Deng San-peng
    [J]. 2020 35TH YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC), 2020, : 854 - 862
  • [3] 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
    [J]. ADVANCED ENGINEERING INFORMATICS, 2022, 54
  • [4] 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
    [J]. Advanced Engineering Informatics, 2022, 54
  • [5] Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing
    Zhou, Guanghui
    Zhang, Chao
    Li, Zhi
    Ding, Kai
    Wang, Chuang
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2020, 58 (04) : 1034 - 1051
  • [6] Intelligent Manufacturing with Digital Twin
    Moeller, Dietmar P. F.
    Vakilzadian, Hamid
    Hou, Weyan
    [J]. 2021 IEEE INTERNATIONAL CONFERENCE ON ELECTRO INFORMATION TECHNOLOGY (EIT), 2021, : 413 - 418
  • [7] Multi-objective coupling optimization of electrical cable intelligent production line driven by digital twin
    Yuan, Gang
    Liu, Xiaojun
    Zhu, Changbiao
    Wang, Chongxin
    Zhu, Minghao
    Sun, Yang
    [J]. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2024, 86
  • [8] Digital twin driven production progress prediction for discrete manufacturing workshop
    Qian, Weiwei
    Guo, Yu
    Zhang, Hao
    Huang, Shaohua
    Zhang, Litong
    Zhou, Hailang
    Fang, Weiguang
    Zha, Shanshan
    [J]. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2023, 80
  • [9] Optimization of Flexible Manufacturing Production Line System Based on Digital Twin
    Ramkumar G.
    Misra S.
    Babu G.R.
    Gottimukkala A.R.
    Siddi S.
    Kumar J.S.
    [J]. SN Computer Science, 4 (5)
  • [10] Sustainability Assessment of Intelligent Manufacturing Supported by Digital Twin
    Li, Lianhui
    Qu, Ting
    Liu, Yang
    Zhong, Ray Y.
    Xu, Guanying
    Sun, Hongxia
    Gao, Yang
    Lei, Bingbing
    Mao, Chunlei
    Pan, Yanghua
    Wang, Fuwei
    Ma, Cong
    [J]. IEEE ACCESS, 2020, 8 : 174988 - 175008