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Extending the Intelligent Digital Twin with a context modeling service: A decision support use case

2022; Elsevier BV; Volume: 107; Linguagem: Inglês

10.1016/j.procir.2022.05.009

2212-8271

Nada Sahlab, Dominik Braun, Christian Köhler, Nasser Jazdi, Michael Weyrich,

IoT and Edge/Fog Computing

Considering the surrounding context of manufacturing systems at runtime enhances their adaptability, which is advantageous given the increasing demand for flexible production. Context-awareness presents a viable approach to continuously model the surrounding context and relate it to the system's operation. As the surrounding context is both acquirable from heterogeneous data sources and is dynamic in nature, a coherent and evolving context model is necessary. The context modeling approach needs to be both: system-centric to enable re-usability of the model by different applications as well as continuously and efficiently extendable to continuously represent the environment. Some approaches to model context within the manufacturing domain exist, but are mostly tailored to specific applications or do not consider an extension at runtime. To include the surrounding context of a system effectively and adapt it accordingly, a relation between the modeled context and the system during runtime is necessary. The intelligent Digital Twin provides essential interdisciplinary models of a physical system, which can be used for its analysis and monitoring. Adding a further service in the form of a model to represent the surrounding context enhances the intelligent Digital Twin to be used by various applications, e.g., for reconfiguration or decision-support. In our previous work, we have presented a tier-based model to realize context-awareness for intelligent Digital Twins. The presented tier model has different levels corresponding to different context scopes. In this contribution, we present an approach to realize an extendible and evolving tier-based context model with a generic ontology and model transformation to a labeled property graph with focus on the external context. To show the applicability and added value of the context model, a use case is presented, which addresses an intelligent warehouse's Digital Twin and its context-model supported decision-making.