From simple digital twin to complex digital twin Part I: A novel modeling method for multi-scale and multi-scenario digital twin

• Published in: Advanced engineering informatics 2022-08, Vol.53, p.101706, Article 101706
• Main Authors: Jia, Wenjie, Wang, Wei, Zhang, Zhenzu
• Format: Article
• Language: English
• Subjects: Complex digital twin; Digital twin modeling; Simple digital twin; Smart manufacturing
• ISSN: 1474-0346; 1873-5320
• DOI: 10.1016/j.aei.2022.101706

In recent years, the digital twin has attracted widespread attention as an important means of digitalization and intelligence. However, the digital twin is becoming more and more complex due to the expansion of need on the simulation of multi-scale and multi-scenario in reality. The instance of digital twin in references mostly concentrates a particular application, while it is still a lack of a method for constructing the complex digital twin in the total elements, the variable scale of working environments, changeable process, not even the coupling effects. In this paper, a novel modeling method for such a complex digital twin is proposed based on the standardized processing on the model division and assembly. Firstly, the complex model of digital twin is divided into several simple models according to the composition, context, component, and code in 4C architecture. Composition and context make the digital twin focus on the effective elements in a specific scale and scenario. Component and code develop the digital twin in standard-based modularization. Secondly, assemble the simple models of digital twins into the complex model through information fusion, multi-scale association and multi-scenarios iterations. Ontology establishes the complete information library of the entities on different digital twins. Knowledge graph bridges the structure relationship between the different scales of digital twins. The scenario iterations realize the behavior interaction and the accuracy calculation results. It provides an implementable method to construct a complex model of digital twin, and the reuse of components and code also enables rapid development of digital twins.