A consistency evaluation method for digital twin models

Digital twin has shown its great application values in various fields in the past few years, especially manufacturing. During the process of digital twin implementation, the digital twin model is one of the most important foundations. Because the effectiveness and accuracy of digital twin models could directly affect the quality of related services. Nowadays, some efforts have been made on digital twin modeling methods, e.g. multi-disciplinary modeling method, multi-dimension modeling method, and multi-scale modeling method. Besides, the research on Industrial Internet of Things makes it possible to realize the synchronization between digital twin models and the corresponding physical objects. However, the attention on how to conduct a comprehensive consistency evaluation between the models and corresponding physical objects is not enough. Against the background, this paper proposed a consistency evaluation framework towards digital twin shop-floor (DTS) models. The consistency evaluation method mainly contains two phases, i.e. before and after model assembly and model fusion. Before model assembly and model fusion, the geometry models, physics models, behavior models, and rule models are mainly considered. After model assembly and fusion, the overall performance of assembled models and fusion models is paid more attention. Furthermore, the analytic hierarchy process(AHP) is used to form a comprehensive consistency evaluation result for DTS models. At last, a specific application scenario in complex product AIT (Assembly, Integration and Test) shop-floor is given to explain how to apply the proposed framework and method.

Automated summary

Digital twin has been widely applied in various fields, especially manufacturing, and the digital twin model is a crucial foundation in the implementation. However, there is insufficient attention on the comprehensive consistency evaluation between the models and physical objects. This paper proposes a consistency evaluation framework and method for digital twin shop-floor models.