IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v35y2024i6d10.1007_s10845-023-02174-5.html
   My bibliography  Save this article

Digital twin enhanced fault diagnosis reasoning for autoclave

Author

Listed:
  • Yucheng Wang

    (Beihang University)

  • Fei Tao

    (Beihang University)

  • Ying Zuo

    (Beihang University)

  • Meng Zhang

    (Tsinghua University)

  • Qinglin Qi

    (Beihang University)

Abstract

Autoclave is the most important equipment in the composite curing process, and its real-time condition has a direct impact on the quality of composite materials. Therefore, rapid and precise fault diagnosis reasoning is of great significance for the autoclave. To address the shortage of signed directed graph (SDG)-based fault diagnosis method, this paper proposes a fault diagnosis method based on digital twin (DT) enhanced SDG for autoclave. Firstly, the SDG model of autoclave temperature control system is constructed, and the model is improved and enhanced by pre-fault transition state identification, fuzzy confirmation of node states, and simplification of potential branch circuits by using DT. The effectiveness of the method in this paper is verified by fault diagnosis based on SDG and DT-SDG methods respectively. The experimental results show that the method proposed in this paper can improve the speed and resolution of fault diagnosis by reducing the number of potential fault propagation paths and the number of inferences.

Suggested Citation

  • Yucheng Wang & Fei Tao & Ying Zuo & Meng Zhang & Qinglin Qi, 2024. "Digital twin enhanced fault diagnosis reasoning for autoclave," Journal of Intelligent Manufacturing, Springer, vol. 35(6), pages 2913-2928, August.
    • Handle: RePEc:spr:joinma:v:35:y:2024:i:6:d:10.1007_s10845-023-02174-5
    DOI: 10.1007/s10845-023-02174-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-023-02174-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-023-02174-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. F. Tao & Y. Cheng & L. Zhang & A. Y. C. Nee, 2017. "Advanced manufacturing systems: socialization characteristics and trends," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1079-1094, June.
    2. 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)

    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. Uwizeyemungu, Sylvestre & Poba-Nzaou, Placide & St-Pierre, Josée, 2022. "Back-end information technology resources and manufacturing SMEs’ export commitment: An empirical investigation," International Business Review, Elsevier, vol. 31(5).
    3. Vendrell-Herrero, Ferran & Bustinza, Oscar F. & Opazo-Basaez, Marco, 2021. "Information technologies and product-service innovation: The moderating role of service R&D team structure," Journal of Business Research, Elsevier, vol. 128(C), pages 673-687.
    4. 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.
    5. Gedas Baranauskas & Agota Giedrė Raišienė & Renata Korsakienė, 2020. "Mapping the Scientific Research on Mass Customization Domain: A Critical Review and Bibliometric Analysis," JRFM, MDPI, vol. 13(9), pages 1-20, September.
    6. Sajjad Rahmanzadeh & Mir Saman Pishvaee & Kannan Govindan, 2023. "Emergence of open supply chain management: the role of open innovation in the future smart industry using digital twin network," Annals of Operations Research, Springer, vol. 329(1), pages 979-1007, October.
    7. Yongzhi Wang & Shaoming Liao & Zhiqun Gong & Fei Deng & Shiyou Yin, 2024. "Enhancing Construction Management Digital Twins Through Process Mining of Progress Logs," Sustainability, MDPI, vol. 16(22), pages 1-29, November.
    8. Xuhui Xia & Wei Liu & Zelin Zhang & Lei Wang & Jianhua Cao & Xiang Liu, 2019. "A Balancing Method of Mixed-model Disassembly Line in Random Working Environment," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
    9. Zhang, Anshan & Wang, Feiliang & Li, Huanyu & Pang, Bo & Yang, Jian, 2024. "Carbon emissions accounting and estimation of carbon reduction potential in the operation phase of residential areas based on digital twin," Applied Energy, Elsevier, vol. 376(PB).
    10. Zio, Enrico & Miqueles, Leonardo, 2024. "Digital twins in safety analysis, risk assessment and emergency management," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    11. Bustinza, Oscar F. & Opazo-Basaez, Marco & Tarba, Shlomo, 2022. "Exploring the interplay between Smart Manufacturing and KIBS firms in configuring product-service innovation performance," Technovation, Elsevier, vol. 118(C).
    12. Jielin Chen & Shuang Li & Hanwei Teng & Xiaolong Leng & Changping Li & Rendi Kurniawan & Tae Jo Ko, 2025. "Digital twin-driven real-time suppression of delamination damage in CFRP drilling," Journal of Intelligent Manufacturing, Springer, vol. 36(2), pages 1459-1476, February.
    13. Daozhi Zhao & Yang Xue & Cejun Cao & Hongshuai Han, 2019. "Channel Selection and Pricing Decisions Considering Three Charging Modes of Production Capacity Sharing Platform: A Sustainable Operations Perspective," Sustainability, MDPI, vol. 11(21), pages 1-28, October.
    14. Quan Xiao & Shanshan Wan & Fucai Lu & Shun Li, 2019. "Risk Assessment for Engagement in Sharing Economy of Manufacturing Enterprises: A Matter–Element Extension Based Approach," Sustainability, MDPI, vol. 11(17), pages 1-29, September.
    15. Chengjun Li & Liguo Yao & Yao Lu & Songsong Zhang & Taihua Zhang, 2025. "DTL-GNN: Digital Twin Lightweight Method Based on Graph Neural Network," Future Internet, MDPI, vol. 17(2), pages 1-24, February.
    16. F. H. Abanda & N. Jian & S. Adukpo & V. V. Tuhaise & M. B. Manjia, 2025. "Digital twin for product versus project lifecycles’ development in manufacturing and construction industries," Journal of Intelligent Manufacturing, Springer, vol. 36(2), pages 801-831, February.
    17. 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.
    18. Evangelos Katsamakas, 2024. "Business models for the simulation hypothesis," Papers 2404.08991, arXiv.org.
    19. Federica Costa & Alberto Portioli-Staudacher, 2021. "Labor flexibility integration in workload control in Industry 4.0 era," Operations Management Research, Springer, vol. 14(3), pages 420-433, December.
    20. Li, Lei & Huang, Haihong & Zou, Xiang & Zhao, Fu & Li, Guishan & Liu, Zhifeng, 2021. "An energy-efficient service-oriented energy supplying system and control for multi-machine in the production line," Applied Energy, Elsevier, vol. 286(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:spr:joinma:v:35:y:2024:i:6:d:10.1007_s10845-023-02174-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.