A Consistency Evaluation Method for Digital Twins in Manufacturing

With the development of emerging technologies such as the Internet of Things and big data, Digital Twin (DT) is increasingly used in manufacturing, and their consistency directly affects the efficiency, quality and reliability of the manufacturing process. This paper proposes a DT consistency evaluation method for smart manufacturing, aiming to solve the problem of maintaining consistency of DT system with physical entities in the manufacturing process. In this paper, the consistency evaluation method is carried out from three dimensions of model consistency, data consistency, and interaction consistency. Combined with the propose of the application, the Analytic Network Process (ANP) is used to weight the indicators and comprehensively assess the consistency of the DT. Taking CNC machine tools as an example, the specific application of this evaluation method is elaborated in detail and its feasibility is verified. The method provides theoretical support for the design and optimization of the DT and helps to promote the further development of intelligent manufacturing.