Leveraging Digital Twins for Compatibility Checks in Production Systems Engineering

In a world driven by short times to market, inconsistencies are highly problematic because they lead to delays. However, the complexity of production systems and the number of disciplines involved increase, resulting in a higher likelihood for inconsistencies. Especially the compatibility between mo...

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Bibliographic Details
Published in2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) pp. 103 - 107
Main Authors Ocker, Felix, Vogel-Heuser, Birgit, Schon, Hauke, Mieth, Robert
Format Conference Proceeding
LanguageEnglish
Published IEEE 13.12.2021
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Summary:In a world driven by short times to market, inconsistencies are highly problematic because they lead to delays. However, the complexity of production systems and the number of disciplines involved increase, resulting in a higher likelihood for inconsistencies. Especially the compatibility between modules is an issue relevant for both design and maintenance. While designers have to integrate appropriate modules into a system, maintenance engineers have to quickly find appropriate replacements if modules fail. Approaches for managing inconsistencies, e.g., using Semantic Web Technologies, have the potential to support both design and maintenance by checking the compatibility of modules. So far, it was cumbersome to aggregate the necessary information for these approaches, but Digital Twins have the potential to resolve this limitation. This paper presents an approach for automating compatibility checks and thus accelerating design and maintenance processes for production systems using a combination of Semantic Web Technologies and Digital Twins. After transforming the systems' Digital Twins into Semantic Digital Twins, Semantic Web Technologies are applied to check compatibility between the production system's modules. The approach is demonstrated via an industrial use case from the special purpose machinery industry.
DOI:10.1109/IEEM50564.2021.9672892