Abstract
In agile Cyber-physical Production System (CPPS) engineering, multi-disciplinary teams work concurrently and iteratively on various CPPS engineering artifacts, based on engineering models and Product-Process-Resource (PPR) knowledge, to design and build a production system. However, in such settings it is difficult to keep track of (i) the effects of changes across engineering disciplines, and (ii) their implications on risks to engineering quality, represented in Failure Mode and Effects Analysis (FMEA). To tackle these challenges and systematically co-evolve FMEA and PPR models, requires propagating and validating changes across engineering and FMEA artifacts. To this end, we design and evaluate a Multi-view FMEA+PPR (MvFMEA+PPR) meta-model to represent relationships between FMEA elements and CPPS engineering assets and trace their change states and dependencies in the design and validation lifecycle. We evaluate the MvFMEA+PPR meta-model in a feasibility study on the quality of a screwing process from automotive production. The study results indicate the MvFMEA+PPR meta-model to be more effective than alternative traditional approaches.
Original language | English |
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Title of host publication | Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2022) |
Subtitle of host publication | 31 August – 2 September 2022 Maspalomas, Gran Canaria, Spain |
Editors | Gustavo M. Callico, Regina Hebig, Andreas Wortmann |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 338-345 |
Number of pages | 8 |
ISBN (Electronic) | 9781665461528 |
ISBN (Print) | 9781665461535 |
DOIs | |
Publication status | Published - 2022 |
Event | 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022 - Gran Canaria, Spain Duration: 31 Aug 2022 → 2 Sept 2022 |
Conference
Conference | 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022 |
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Country/Territory | Spain |
City | Gran Canaria |
Period | 31/08/22 → 2/09/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- agile cyber-physical production system engineering
- failure mode and effects analysis
- multi-disciplinary engineering
- multi-view modeling
- product process resource knowledge