Biffl, S., Kropatschek, S., Kiesling, E., Meixner, K., & Lüder, A. (2022). Risk-Driven Derivation of Operation Checklists from Multi-Disciplinary Engineering Knowledge. In 2022 IEEE 20th International Conference on Industrial Informatics (INDIN) (pp. 7–14). https://doi.org/10.1109/INDIN51773.2022.9976096
E194-01 - Forschungsbereich Software Engineering E194-04 - Forschungsbereich Data Science
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Published in:
2022 IEEE 20th International Conference on Industrial Informatics (INDIN)
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ISBN:
978-1-7281-7568-3
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Date (published):
2022
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Event name:
20th IEEE International Conference on Industrial Informatics, INDIN 2022
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Event date:
25-Jul-2022 - 28-Jul-2022
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Event place:
Perth, Australia
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Number of Pages:
8
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Peer reviewed:
Yes
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Keywords:
Production Systems Engineering; Industry 4.0; Process FMEA; PPR; Skills; Digitalization
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Abstract:
During the ramp-up of a production system, complex and difficult to resolve product quality issues often result in
tedious experimentation and costly delays. A particular challenge
in this context is insufficient guidance for operators on how to
resolve issues and adapt their actions to a new production context.
Failure Mode and Effects Analysis (FMEA) can help to identify
and address likely causes of production quality issues. However,
FMEA models are typically (i) isolated from engineering domain
models on product, process and resource (PPR) concerns, and (ii)
not actionable for operators. This paper introduces the FMEAto-Operation (F2O) approach to reduce the risk of ramp-up
delays and recurring quality issues by integrating the required
domain knowledge for model-driven, machine skill-centric, and
actionable process FMEA. The F2O approach (i) validates likely
root causes of a production quality issue by linking these causes to
engineering reality in a graph database, and (ii) derives operation
checklists with prioritized countermeasures. In a feasibility study
on a real-world welding cell for car parts, we evaluated the
effectiveness and efficiency of the F2O approach. Results indicate
that the F2O approach is feasible and effective, and provides
operators with actionable, context-specific guidelines that are well
grounded in engineering models.
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Project title:
Verbesserung der Sicherheit von Informationsprozessen in Produktionssystemen: CDL SQI (CDG Christian Doppler Forschungsgesellschaft; CDG Christian Doppler Forschungsgesellschaft)
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Project (external):
ffg
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Project ID:
881843
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Research Areas:
Computer Engineering and Software-Intensive Systems: 50% Information Systems Engineering: 50%