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An accuracy and performance-oriented accurate digital twin modeling method for precision microstructures

Author

Listed:
  • Qimuge Saren

    (Beijing Institute of Technology)

  • Zhijing Zhang

    (Beijing Institute of Technology)

  • Jian Xiong

    (Beijing Institute of Technology)

  • Xiao Chen

    (Beijing Institute of Technology)

  • Dongsheng Zhu

    (Beijing Institute of Technology)

  • Wenrong Wu

    (China Academy of Engineering Physics)

  • Xin Jin

    (Beijing Institute of Technology)

  • Ke Shang

    (Beijing Institute of Technology)

Abstract

Digital twin, a core technology for intelligent manufacturing, has gained extensive research interest. The current research was mainly focused on digital twin based on design models representing ideal geometric features and behaviors at macroscopic scales, which is challenging to accurately represent accuracy and performance. However, a numerical representation is essential for precision microstructures whose accuracy and performance are difficult to measure. The concept of a digital twin for an accurate representation, proposed in 2015, is still in the conceptual stage without a clear construction method. Therefore, the goal of accurate representation has not been achieved. This paper defines the concept and connotation of an accuracy and performance-oriented accurate digital twin model and establishes its architecture in two levels: geometric and physical. First, a geometric digital twin model is constructed by the contact surfaces distributed error modeling and virtual assembly with nonuniform contact states. Then, based on this, a physical digital twin model is constructed by considering the linear and nonlinear response of the structural internal physical properties to the external environment and time to characterize the accuracy and performance variation. Finally, the models are evaluated. The method is validated on microtarget assembly. The estimated values of surface modeling, center offset, and stress prediction accuracy are 94.22%, 89.3%, and 83.27%. This paper provides a modeling methodology for the digital twin research to accurately represent accuracy and performance, which is critical for product quality improvements in intelligent manufacturing. Research results can be extended to larger-scale precision structures for performance prediction and optimization.

Suggested Citation

  • Qimuge Saren & Zhijing Zhang & Jian Xiong & Xiao Chen & Dongsheng Zhu & Wenrong Wu & Xin Jin & Ke Shang, 2024. "An accuracy and performance-oriented accurate digital twin modeling method for precision microstructures," Journal of Intelligent Manufacturing, Springer, vol. 35(6), pages 2887-2911, August.
    • Handle: RePEc:spr:joinma:v:35:y:2024:i:6:d:10.1007_s10845-023-02169-2
    DOI: 10.1007/s10845-023-02169-2
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    References listed on IDEAS

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    1. Jinjiang Wang & Lunkuan Ye & Robert X. Gao & Chen Li & Laibin Zhang, 2019. "Digital Twin for rotating machinery fault diagnosis in smart manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3920-3934, June.
    2. Michael W. Grieves, 2005. "Product lifecycle management: the new paradigm for enterprises," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 2(1/2), pages 71-84.
    3. Xin Tong & Qiang Liu & Shiwei Pi & Yao Xiao, 2020. "Real-time machining data application and service based on IMT digital twin," Journal of Intelligent Manufacturing, Springer, vol. 31(5), pages 1113-1132, June.
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