Model-driven digital twin construction

Abstract

Digital twins emerge in many disciplines to support engineering, monitoring, controlling, and optimizing cyber-physical systems, such as airplanes, cars, factories, medical devices, or ships. There is an increasing demand to create digital twins as representation of cyber-physical systems and their related models, data traces, aggregated data, and services. Despite a plethora of digital twin applications, there are very few systematic methods to facilitate the modeling of digital twins for a given cyber-physical system. Existing methods focus only on the construction of specific digital twin models and do not consider the integration of these models with the observed cyber-physical system. To mitigate this, we present a fully model-driven method to describe the software of the cyber-physical system, its digital twin information system, and their integration. The integration method relies on MontiArc models of the cyber-physical system's architecture and on UML/P class diagrams from which the digital twin information system is generated. We show the practical application and feasibility of our method on an IoT case study. Explicitly modeling the integration of digital twins and cyber-physical systems eliminates repetitive programming activities and can foster the systematic engineering of digital twins.