Risk-Driven Derivation of Operation Checklists from Multi-Disciplinary Engineering Knowledge

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.