Reference architecture for digital twin-based predictive maintenance systems

Digital Twin-based predictive maintenance systems are frequently integrated into complex systems. The success of the integration depends on the design of the system. A Reference Architecture can be used as a blueprint to design Application Architectures rapidly and consistently for various application domains, resulting in a reduced time-to-market. The main objective of this study is to develop and evaluate a Reference Architecture designed using renowned software architecture methods. A domain analysis was performed to gather and synthesize the literature on Digital Twin-based predictive maintenance systems, which we used to model the key features. We applied UML diagrams to design the reference architecture based on the feature model. We evaluated the reference architecture using three case studies. We derived three views for Digital Twin-based predictive maintenance systems. For the user's view, we developed a context diagram. We developed a package diagram for the structural view, and we designed a layered view to show the system's decomposition in layers. We designed an Application Architecture for each case study based on the study's features using each Reference Architecture view. Additionally, we designed a deployment view to describe the hardware and software and its environment. We demonstrated that the methods of creating a Reference Architecture could be used in the Digital Twin-based predictive maintenance domain and showed how an Application Architecture could be designed in this context.