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Enhancing Digital Shadows with Workflows
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2022
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Gesellschaft für Informatik e.V.
Zusammenfassung
The vast amount of data in modern manufacturing demands acquisition of contextualized data to enable fast decision making where domain expertise must be provided at run-time. Within this paper, we investigate the research question how to handle human-machine-interactions for engineering of digital shadows and still ensure the traceability of computation and simulation results. Current research for digital shadows concentrates on modeling key elements such as data sharing or metadata, but does not incorporate human-machine-interaction or the traceability of data aggregation. In this paper, we present a conceptual model which covers the base concepts for digital shadows integrating human-machine-interaction by utilizing workflows. We extend the conceptual digital shadow model defined within the “Internet of Production” excellence cluster and showcase our approach on an example. This contribution presents an applicable modeling approach for designing digital shadows which provide contextual information of the underlying human integrated process.