# Digital Twin Model Quality Optimization and Control Methods Based on Workflow Management
## 2 Overview  
Digital twin modeling is a highly complex process involving knowledge in multiple disciplines and domains, and requiring consideration of all aspects of model validity, generality, and efficiency. The modeling is usually conducted step by step in a collaborative design process by teams of engineers with different disciplinary backgrounds. However, the results of digital twin model construction are difficult to estimate during the collaborative design process, rendering it challenging to control model quality at each stage and effectively allocate solutions to improve model quality. Due to the above problems, digital twin model quality issues often emerge and draw attention in the application and maintenance phases.  
Based on the current state of digital twin model quality studies and digital twin model construction, this study proposes a workflow management-based digital twin model quality optimization and control method to effectively apply a wide variety of digital twin model evaluation methods and optimization solutions. The proposed method integrates the digital twin modeling process into the workflow of product data management (PDM) [18; 19] so that the flow of the model in the workflow can be controlled at the macro level through workflow techniques in the design process, and the model quality optimization can be supported at the micro level. The operation framework is shown in Figure 1. The main steps of the proposed method are as follows: First, the initial files of the model are inputted into the PDM's workflow integrated with digital twin model evaluation. Then, through macro-level model quality control, and based on workflow management, the qualified digital twin model continues its flow, leaving the unqualified digital twin models at the current workflow node. If an abnormal index is found in the macro control, the model quality is optimized through micro-level model quality optimization methods by selecting the solution for the abnormal index. Finally, the above process is repeated until the model is archived in the workflow, at which moment the digital twin model of acceptable quality is outputted.  
The innovation of this study is to integrate a wide variety of model evaluation indexes and optimization solutions into the workflow for digital twin model quality optimization and control, which is of great value for shortening the product development lifecycle and promoting the development of enterprise information management. The contributions of this study are as follows:  
1. From a macro perspective, a digital twin model quality control method based on workflow management is proposed.
2. Referring to the biological immunity process, a micro-level digital twin model quality optimization method is proposed.
3. A digital twin model quality control optimization method incorporating macro-control and micro-optimization is proposed.  
Figure 1: Digital twin model quality optimization and control method based on workflow management.  
The rest of this article is structured as follows: Section 2 provides a general overview. The modeling of the workflow integrated with model evaluation is presented in Section 3. The digital twin model quality optimization and control method is described in Sections 4 and 5. Section 6 presents the experimental results and analysis. The discussion is in Section 7. Section 8 is the conclusion.