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Rapid simplification of 3D geometry model of mechanisms in the digital twins-driven manufacturing system design

Author

Listed:
  • Jiewu Leng

    (Guangdong University of Technology
    Guangdong University of Technology)

  • Zisheng Lin

    (Guangdong University of Technology)

  • Zhiqiang Huang

    (Guangdong University of Technology)

  • Ruijun Ye

    (Guangdong University of Technology)

  • Qiang Liu

    (Guangdong University of Technology
    Guangdong University of Technology)

  • Xin Chen

    (Guangdong University of Technology)

Abstract

With the development of simulation technology, more and more manufacturers have begun to use the digital twin to design workshops and factories. For these design scenarios under real-time interaction requirements with an excessive amount of model data, if the rendering is stuck, it will reduce the work efficiency. It is a key enabling technology to simplify and switch the geometry models with different resolutions, according to the distance of the viewpoint or the motion state to reduce the computational complexity. Existing model simplification methods emphasize the universality and efficiency under various scenarios, while the simplification performance in the 3D geometry models of industrial mechanisms is poor. This paper proposes a rapid simplification approach to the 3D geometry model of mechanisms in the digital twins-driven manufacturing system design context. A novel Vertex Saliency-oriented Classified Edge Collapse (VS-CEC) algorithm is proposed to simplify the shape feature of the 3D geometry model of mechanisms. It especially emphasizes solving the sharp shape preservation issues in the mechanical design scenario rather than a universal things design scenario. A vertex saliency factor is defined and integrated with the region boundary information obtained from the processing of detailed features to ensure visual fidelity as well as shape preservation such as sharp edges. Experiments show that this approach reduces the data model complexity more reasonably to speed up the rendering. It ensures that the digital twin model interacts quickly with the physical manufacturing system, and thus realizes the low-latency visual effect of cyber-physical synchronization.

Suggested Citation

  • Jiewu Leng & Zisheng Lin & Zhiqiang Huang & Ruijun Ye & Qiang Liu & Xin Chen, 2024. "Rapid simplification of 3D geometry model of mechanisms in the digital twins-driven manufacturing system design," Journal of Intelligent Manufacturing, Springer, vol. 35(6), pages 2765-2786, August.
  • Handle: RePEc:spr:joinma:v:35:y:2024:i:6:d:10.1007_s10845-023-02178-1
    DOI: 10.1007/s10845-023-02178-1
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    References listed on IDEAS

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    1. Konstantinos Mykoniatis & Gregory A. Harris, 2021. "A digital twin emulator of a modular production system using a data-driven hybrid modeling and simulation approach," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1899-1911, October.
    2. Chih-Hsing Chu & Cheng-Hung Lo & Han-Chung Cheng, 2017. "Cognitive shape similarity assessment for 3D part search," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1679-1694, October.
    3. Giampaolo Campana & Mattia Mele, 2020. "An application to Stereolithography of a feature recognition algorithm for manufacturability evaluation," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 199-214, January.
    4. Qiang Liu & Hao Zhang & Jiewu Leng & Xin Chen, 2019. "Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3903-3919, June.
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