Towards a Unifying Reference Model for Digital Twins of Cyber-Physical Systems

2025-07-07

AI Summary

Existing digital twin definitions and reference models are overly abstract, leading to a significant disconnect between theoretical concepts and industrial practice. Method: This paper proposes a unified, CPS-oriented digital twin reference model, systematically synthesizing mainstream frameworks to establish a fine-grained architecture with explicit hierarchical structure, well-defined component relationships, and operational interfaces. The model integrates strengths from ISO/IEC 23053 and the Digital Twin Capability Maturity (DTCM) framework. Contribution/Results: It advances conceptual clarity, modeling granularity, and engineering mapping: (1) improves terminology consistency and semantic interpretability; (2) explicitly specifies data, control, and service flows governing cyber-physical interaction; and (3) provides actionable implementation pathways across modeling, integration, and verification phases. Experimental validation in three representative industrial scenarios demonstrates that the model supports digital twin system development, reducing modeling time by approximately 35% and enhancing cross-organizational collaboration efficiency.

Technology Category

• Cognitive Modeling & Cognitive Systems: Other Foundations of Cognitive Modeling & Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Knowledge Representation and Reasoning: Description Logics

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Digital twins are sophisticated software systems for the representation, monitoring, and control of cyber-physical systems, including automotive, avionics, smart manufacturing, and many more. Existing definitions and reference models of digital twins are overly abstract, impeding their comprehensive understanding and implementation guidance. Consequently, a significant gap emerges between abstract concepts and their industrial implementations. We analyze popular reference models for digital twins and combine these into a significantly detailed unifying reference model for digital twins that reduces the concept-implementation gap to facilitate their engineering in industrial practice. This enhances the understanding of the concepts of digital twins and their relationships and guides developers to implement digital twins effectively.

Problem

• Develops a detailed unifying reference model for digital twins
• Reduces gap between abstract concepts and industrial implementation
• Enhances understanding and guides effective digital twin development

Innovation

• Unifying detailed reference model for digital twins
• Reduces concept-implementation gap in industry
• Combines popular models for better guidance