Multidimensional Data Modeling and Model Validation for Digital Twin Workshop

Digital twin workshop (DTW) is an important embodiment of intelligent manufacturing in the workshop level, which enables the smart production control and management of the workshop. However, there still exist problems including data modeling and verification of digital model in the process of DTW construction. To solve these problem, multidimensional data modeling and model validation methods of DTW are proposed in this article. First, five-order tensor models for representing manufacturing elements are established to unify the data from physical workshop (PW) and virtual workshop (VW). Then, the mathematical method for verifying DTW twin model is proposed from the recessive and explicit perspective. Finally, a case study of an aerospace machining workshop is carried out to verify the operability and effectiveness of the proposed method. The case analysis shows that the proposed methods can effectively evaluate whether the twin model accurately provides the description of the actual behavior process of physical workshop, and the proposed methods have good performance.

Automated summary

This article proposes multidimensional data modeling and model validation methods for digital twin workshop (DTW), which effectively solves problems in intelligent manufacturing at the workshop level by establishing fifth-order tensor models and proposing mathematical verification methods.