A Model-Based Framework for Developing DTs in Industry 4.0

2026-07-03

AI Summary

This study addresses the challenges of non-standardized, time-consuming, and resource-intensive digital twin development by proposing a tool-supported framework that, for the first time, enables the automatic derivation of purpose-specific digital twins from existing engineering models. By reusing pre-existing structural and behavioral models of physical assets and integrating lightweight customization and configuration, the approach leverages model-based engineering methods and automated generation techniques to rapidly align digital twins with operational objectives. The framework’s feasibility, generality, and engineering practicality are demonstrated through the successful automatic generation of digital twin instances across four heterogeneous use cases.

Abstract

With the rise of Industry 4.0 driven by the integration of Cyber-Physical Systems (CPS) and the Internet of Things (IoT), the use of Digital Twins (DTs) has significantly increased over the past decade, as they provide detailed insights and support well-informed decision-making. However, the lack of standardized methodologies, in addition to the time and resources involved for building them remains an important challenge. Building on the idea that engineering models of the physical twin (PT) are often available, we propose a tool-supported framework that automates the derivation of DTs by leveraging existing structural and behavioral models of the PT and extending them with additional models to build a comprehensive DT. To demonstrate the feasibility of our approach, we applied it to four different use cases, in which we automatically derived DT instances from (1) models of their PT, (2) configuration of our generic framework and (3) minimal ad hoc additional development for connecting the DT to the PT. These experiments illustrate the applicability of our framework for building DTs in contexts that satisfy our assumptions and requirements. By simply configuring the framework, we are able to derive a DT aligned with its operational purpose.

Problem

• Digital Twin
• Industry 4.0
• Standardization
• Model-Based Development
• Cyber-Physical Systems

Innovation

• Digital Twin
• Model-Based Framework
• Automation
• Cyber-Physical Systems
• Industry 4.0