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Modelling and online training method for digital twin workshop

Author

Listed:
  • Litong Zhang
  • Yu Guo
  • Weiwei Qian
  • Weili Wang
  • Daoyuan Liu
  • Sai Liu

Abstract

Aiming at the difficulties in modelling, simulation and verification in digital twin workshop, a modelling and online training method for digital twin workshop is proposed. This paper describes a multi-level digital twin aggregate modelling method, including the status attributes, the static performance attributes and the fluctuation performance attributes, and designs a digital twin organisation system, namely, digital twin graph. According to the data demand for digital twin aggregates, a spatio-temporal data model is constructed. The digital twin model training method using truncated normal distribution is presented. Furthermore, a verification method based on real-virtual error for a digital twin model is proposed. The effectiveness of real-time status monitoring, online model training and simulation for production is verified by a case.

Suggested Citation

  • Litong Zhang & Yu Guo & Weiwei Qian & Weili Wang & Daoyuan Liu & Sai Liu, 2023. "Modelling and online training method for digital twin workshop," International Journal of Production Research, Taylor & Francis Journals, vol. 61(12), pages 3943-3962, June.
    • Handle: RePEc:taf:tprsxx:v:61:y:2023:i:12:p:3943-3962
    DOI: 10.1080/00207543.2022.2051088
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