TY - GEN
T1 - Leveraging Digital Twins for Compatibility Checks in Production Systems Engineering
AU - Ocker, Felix
AU - Vogel-Heuser, Birgit
AU - Schon, Hauke
AU - Mieth, Robert
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Compatibility
KW - Digital twin
KW - Inconsistency management
UR - http://www.scopus.com/inward/record.url?scp=85125366291&partnerID=8YFLogxK
U2 - 10.1109/IEEM50564.2021.9672892
DO - 10.1109/IEEM50564.2021.9672892
M3 - Conference contribution
AN - SCOPUS:85125366291
T3 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
SP - 103
EP - 107
BT - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Y2 - 13 December 2021 through 16 December 2021
ER -