Risk and Engineering Knowledge Integration in Cyber-physical Production Systems Engineering

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.