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Multidimensional information model-driven digital twin for the intelligent evaluation of production capacity

  • Zhang Lu,
  • He Songping,
  • Li Bin,
  • Mao Xinyong,
  • Tan Xin

摘要

The digital twin (DT) for application development in specific fields or specific factors has emerged as a foundational framework for intelligent manufacturing. The increasing demand for customized and diverse production poses enormous challenges for the effective evaluation of production line processing capability (PLPC). Therefore, this paper presents a multidimensional information model-driven digital twin specifically designed for PLPC evaluation. The information model describes the characteristics of PLPC in the structural, physical, and kinematic dimensions, and it provides multidimensional information for constructing a comprehensive evaluation model in combination with the fuzzy Delphi method. An information model-driven digital twin enables more efficient extraction of processing capabilities relevant to product manufacturing and provides a digital and visual assessment of PLPC. In the case of the commutator processing industry, this paper highlights the feasibility of the digital twin model and its potential impact on forward-looking guidance for product process planning.