A Blueprint Of Digital Twins In High Volume Production Environments Using The Asset Administration Shell

Abstract

Digital twins in production environments enable a structured and uniform access to distributed asset-related data, functionalities and models, which can be leveraged by applications to achieve a sustainable improvement of the manufacturing system. However, production environments are complex and contain various heterogeneous and highly interrelated asset types, making its digital representation through digital twins difficult and ambiguous. Given this situation, we introduce a concept for a structured implementation of digital twins in production environments using the Asset Administration Shell (AAS). First, relevant types of production assets, which are associated with an AAS, are derived. In the next step, the identified asset types are characterized, relationships are defined and thus a coherent concept for the digital representation of production environments is created. Finally, an approach for applying the concept in high-volume production is described. We then validate our approach conceptually using the example of a lab-scale production environment for battery cell manufacturing. By introducing a concept to structure and scale the use of the AAS, we aim to simplify the conceptual design of AASs for the digital representation of (high-volume) production environments, to enhance data-driven improvements.