Abstract
The concept of digital twins (DT) has already been discussed some decades ago. Digital representations of physical assets are key components in industrial applications as they are the basis for decision making. What is new is the conceptual approach to consider DT as well-defined software entities themselves that follow the whole lifecycle of their physical counterparts from the engineering, operation up to the discharge, and hence, have their own type description, identity, and lifecycle. This paper elaborates on this idea and argues the need for systematic DT engineering and management. After a conceptual description of DT, the paper proposes a DT lifecycle model and presents methodologies and tools for DT management, also in the context of Industrie 4.0 concepts, such as the asset administration shell (AAS), the international data spaces (IDS), and IEC standards (such as OPC UA and AML). As a tool example for the support of DT engineering and management, the Fraunhofer-advanced AAS tools for digital twins (FA3ST) are presented in more detail.
Highlights
While people are mainly interested in services provided by a digital twins (DT), for the hardware and software systems DT functionalities should be available via an application programming interfaces (APIs)
While this paper identified four essential categories to form a technology stack that ensures a coherent and consistent DT implementation, we showed how this was realized based on the PI4.0 administration shell (AAS)
Our intention is to conceptualize methods and tools that support the whole lifecycle of a DT, from identification to modelling, development, sharing, use, and continuous improvement
Summary
Representations of real-world objects as digital models have been an innate topic of computer science. Complimentary to the processing close to the device, there is the option to store asset data in a cloud environment where it may be processed over the whole lifetime of an asset following the different business models of the engineering, operation and discharge phases. This means that, apart from the question of adequate modelling for given use cases, the management of digital twins (e.g., lifecycle management, versioning, interoperability issues) is getting more and more demanding (e.g., [2,3,4], see Section 6).
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