Abstract
Smart manufacturing demands to process data in domain-specific real-time. Engineering models created for constructing, commissioning, planning, or simulating manufacturing systems can facilitate aggregating and abstracting the wealth of manufacturing data to faster processable data structures for more timely decision making. Current research lacks conceptual foundations for how data and engineering models can be exploited in an integrated way to achieve this. Such research demands expertise from different smart manufacturing domains to harmonize the notion space. We propose a conceptual model to describe digital shadows, data structures tailored to exploit models and data in smart manufacturing, through a metamodel and its notion space. This conceptual model was established through interdisciplinary research in the German excellence cluster “Internet of Production” and evaluated in various real-world manufacturing scenarios. This foundation for an understanding helps to manage complexity, automated analyses, and syntheses, and, ultimately, facilitates cross-domain collaboration.
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Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2023 Internet of Production - 390621612. Website: https://www.iop.rwth-aachen.de/.
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Becker, F. et al. (2021). A Conceptual Model for Digital Shadows in Industry and Its Application. In: Ghose, A., Horkoff, J., Silva Souza, V.E., Parsons, J., Evermann, J. (eds) Conceptual Modeling. ER 2021. Lecture Notes in Computer Science(), vol 13011. Springer, Cham. https://doi.org/10.1007/978-3-030-89022-3_22
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