An Expandable and Generalized Method for Equipment Information Reflection in Digital Twin Workshop Systems

A production workshop is equipped with diverse equipment and machinery, and manufacturing data generated by different equipment show certain differences. Therefore, developing a method with an information presentation capability for a digital twin workshop system (DTWS) can be challenging due to the numerous information sources and types. The level of detail provided for a DTWS is directly related to the management comprehension of the production status of a physical workshop. Thus, arranging and presenting different data effectively represents a significant challenge. To address this challenge, this study proposes an equipment information selfreflection method with expandability for DTWSs. First, a generic equipment information model with an expandability is developed. This model encompasses all relevant data types in a workshop. The analysis of these data is conducted from two perspectives: workshop equipment categorization and equipment internal composition. The analysis results are used for the generation of extensible styles for property elements and function components. For the DTWSs, these two perspectives offer a standardized specification for equipment information presentation. In addition, a self-reflection method is introduced to address the demand for generating diverse information types ranging from equipment-based to extensible types. The system framework and operational flow of this method are explained in detail. To verify the proposed method, this paper conducts a practical case study using the DTWorks software development kit to simulate a real workshop. The proposed self-reflection method is implemented into the DTWorks. The disparities in equipment information types are analyzed for both pre- and post-implementation of the proposed method. The obtained results demonstrate the efficiency and advantages of the proposed self-reflection method. Finally, the results show that the proposed method exhibits advantageous performance regarding intricate business contexts.