TY - GEN
T1 - A Framework for Inconsistency Detection Across Heterogeneous Models in Industry 4.0
AU - Zou, M.
AU - Li, H.
AU - Vogel-Heuser, B.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Manufacturing systems nowadays get more interconnected and flexible. Developing such a system appeals for closer interdisciplinary collaboration. Various models are used by different engineers to shape specific views on the system, but might also introduce contradictions, i.e. inconsistencies, leading to engineering delays or failures. This study proposes a knowledge-based framework to detect and avoid inconsistency across models representing different views of the same system. A prototype of the framework is implemented and evaluated.
AB - Manufacturing systems nowadays get more interconnected and flexible. Developing such a system appeals for closer interdisciplinary collaboration. Various models are used by different engineers to shape specific views on the system, but might also introduce contradictions, i.e. inconsistencies, leading to engineering delays or failures. This study proposes a knowledge-based framework to detect and avoid inconsistency across models representing different views of the same system. A prototype of the framework is implemented and evaluated.
KW - Inconsistency
KW - Knowledge Base
KW - Manufacturing System Development
KW - Model-based Engineering
UR - http://www.scopus.com/inward/record.url?scp=85079668393&partnerID=8YFLogxK
U2 - 10.1109/IEEM44572.2019.8978930
DO - 10.1109/IEEM44572.2019.8978930
M3 - Conference contribution
AN - SCOPUS:85079668393
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 29
EP - 34
BT - 2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
PB - IEEE Computer Society
T2 - 2019 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2019
Y2 - 15 December 2019 through 18 December 2019
ER -