IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i9p7690-d1141495.html
   My bibliography  Save this article

Visualization Monitoring of Industrial Detonator Automatic Assembly Line Based on Digital Twin

Author

Listed:
  • Hongjun Li

    (Hubei Engineering Research Center of Industrial Detonator Intelligent Assembly, Wuhan 430073, China
    School of Mechanical Engineering and Automation, Wuhan Textile University, Wuhan 430073, China)

  • Yu Yang

    (Hubei Engineering Research Center of Industrial Detonator Intelligent Assembly, Wuhan 430073, China
    School of Mechanical Engineering and Automation, Wuhan Textile University, Wuhan 430073, China)

  • Chi Zhang

    (Hubei Engineering Research Center of Industrial Detonator Intelligent Assembly, Wuhan 430073, China
    School of Mechanical Engineering and Automation, Wuhan Textile University, Wuhan 430073, China)

  • Chengjun Zhang

    (Hubei Engineering Research Center of Industrial Detonator Intelligent Assembly, Wuhan 430073, China
    School of Mechanical Engineering and Automation, Wuhan Textile University, Wuhan 430073, China)

  • Wei Chen

    (School of Mechanical Engineering and Automation, Wuhan Textile University, Wuhan 430073, China)

Abstract

The continuous development of information technology has increased the level of automation and informatization in the manufacturing industry, which makes it necessary for companies to effectively monitor their assembly lines. Aiming to visualize the monitoring challenges of the assembly line production process, taking the industrial detonator automatic assembly line as the research object and referring to the digital twin five-dimensional model, a visualization monitoring method that utilizes an assembly line based on a digital twin is proposed. First, the architecture of the assembly line visualization monitoring system based on digital twin is constructed, and its specific operation flow is studied. Then, three key implementation methods, including assembly line virtual entity model construction, data collection in the assembly process and complex equipment error detection, are studied. Finally, a visualization monitoring system for the industrial detonator automatic assembly line is designed and developed, which verifies that the proposed method is effective in the visualization monitoring of the assembly line.

Suggested Citation

  • Hongjun Li & Yu Yang & Chi Zhang & Chengjun Zhang & Wei Chen, 2023. "Visualization Monitoring of Industrial Detonator Automatic Assembly Line Based on Digital Twin," Sustainability, MDPI, vol. 15(9), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7690-:d:1141495
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/9/7690/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/9/7690/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fei Tao & Qinglin Qi, 2019. "Make more digital twins," Nature, Nature, vol. 573(7775), pages 490-491, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Weng Siew Lam & Weng Hoe Lam & Pei Fun Lee, 2023. "A Bibliometric Analysis of Digital Twin in the Supply Chain," Mathematics, MDPI, vol. 11(15), pages 1-24, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jian-Guo Duan & Tian-Yu Ma & Qing-Lei Zhang & Zhen Liu & Ji-Yun Qin, 2023. "Design and application of digital twin system for the blade-rotor test rig," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 753-769, February.
    2. Xinzhou Wu & Zhe Cheng & Victor E. Kuzmichev, 2023. "Dynamic Fit Optimization and Effect Evaluation of a Female Wetsuit Based on Virtual Technology," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    3. Zio, Enrico & Miqueles, Leonardo, 2024. "Digital twins in safety analysis, risk assessment and emergency management," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    4. Evangelos Katsamakas, 2024. "Business models for the simulation hypothesis," Papers 2404.08991, arXiv.org.
    5. Dapai Shi & Jingyuan Zhao & Chika Eze & Zhenghong Wang & Junbin Wang & Yubo Lian & Andrew F. Burke, 2023. "Cloud-Based Artificial Intelligence Framework for Battery Management System," Energies, MDPI, vol. 16(11), pages 1-21, May.
    6. Xueru Zhang & Dennis K. J. Lin & Lin Wang, 2023. "Digital Triplet: A Sequential Methodology for Digital Twin Learning," Mathematics, MDPI, vol. 11(12), pages 1-16, June.
    7. Milena Kajba & Borut Jereb & Tina Cvahte Ojsteršek, 2023. "Exploring Digital Twins in the Transport and Energy Fields: A Bibliometrics and Literature Review Approach," Energies, MDPI, vol. 16(9), pages 1-23, May.
    8. Bai, Fan & Quan, Hong-Bing & Yin, Ren-Jie & Zhang, Zhuo & Jin, Shu-Qi & He, Pu & Mu, Yu-Tong & Gong, Xiao-Ming & Tao, Wen-Quan, 2022. "Three-dimensional multi-field digital twin technology for proton exchange membrane fuel cells," Applied Energy, Elsevier, vol. 324(C).
    9. Jaljolie, Ruba & Riekkinen, Kirsikka & Dalyot, Sagi, 2021. "A topological-based approach for determining spatial relationships of complex volumetric parcels in land administration systems," Land Use Policy, Elsevier, vol. 109(C).
    10. Muhammad Ali Musarat & Alishba Sadiq & Wesam Salah Alaloul & Mohamed Mubarak Abdul Wahab, 2022. "A Systematic Review on Enhancement in Quality of Life through Digitalization in the Construction Industry," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    11. Chao Ke & Xiuyan Pan & Pan Wan & Zixi Huang & Zhigang Jiang, 2023. "An Intelligent Redesign Method for Used Products Based on Digital Twin," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    12. Dianyou Yu & Zheng He, 2022. "Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: advances, challenges, and opportunities," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 1-36, May.
    13. Farzam Farbiz & Mohd Salahuddin Habibullah & Brahim Hamadicharef & Tomasz Maszczyk & Saurabh Aggarwal, 2023. "Knowledge-embedded machine learning and its applications in smart manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 2889-2906, October.
    14. Pin Wu & Lulu Ji & Wenyan Yuan & Zhitao Liu & Tiantian Tang, 2023. "A Digital Twin Framework Embedded with POD and Neural Network for Flow Field Monitoring of Push-Plate Kiln," Future Internet, MDPI, vol. 15(2), pages 1-20, January.
    15. Jieyin Lyu & Shouqin Zhou & Jingang Liu & Bingchun Jiang, 2023. "Intelligent-Technology-Empowered Active Emergency Command Strategy for Urban Hazardous Chemical Disaster Management," Sustainability, MDPI, vol. 15(19), pages 1-28, September.
    16. Majidi Nezhad, Meysam & Neshat, Mehdi & Sylaios, Georgios & Astiaso Garcia, Davide, 2024. "Marine energy digitalization digital twin's approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7690-:d:1141495. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.