A generic digital twin model construction strategy for cross-field implementations with comprehensiveness, operability and scalability

Abstract

In recent years, the prominence of Digital Twins as pivotal tools in digitization and intelligence has sparked widespread interest. However, the diversity of Digital Twin applications has led to a plethora of evolving technologies, standards, and building methods. These varying terms and frequent incompatibilities necessitate a unified approach to characterize and craft Digital Twin models. This endeavor aims not only to streamline construction processes but also to ensure the reusability and collaboration of Digital Twin models across diverse scenarios. This work proposes Digital twin model building strategy (DTBS), deriving four key processes for constructing digital twin models from the perspective of application scenarios: based on physical entities, twin service requirements, physical data, and entity requirements. Subsequently, by defining the application scenarios and employing suitable strategies, the building of digital twin models is accomplished. The DTBS serves as the core strategy for the building of digital twin models, guiding the complete construction process of digital twin models. The DTBS aims to achieve three objectives: comprehensiveness (encompassing all stages of digital twin model building), operability (with low thresholds for researchers and practitioners), and scalability (encompassing not just one scenario, but multiple domains). Additionally, through case studies, the effectiveness of the Digital twin model building strategy in practical engineering contexts is expounded upon. This strategy's strength lies in its ability to maintain scalability while also demonstrating comprehensiveness and operability.