Advancing PFMEA Decision-Making: FRADAR Based Prioritization of Failure Modes Using AP, RPN, and Multi-Attribute Assessment in the Automotive Industry

Abstract

This research proposes a novel way to improve Process Failure Modes and Effects Analysis (PFMEA) by using the Fuzzy RAnking based on the Distances And Range (FRADAR) method to prioritize activities for mitigating or eliminating failure modes in the automotive industry. The suggested approach seeks to improve classic PFMEA by using fuzzy sets to better assess risk-related criteria and their inherent uncertainty. The criteria used to prioritize actions for mitigating failure modes include the Action Priority (AP) and Risk Priority Number (RPN) approach, as well as the cost-effectiveness of actions, the time required to resolve issues, and their impact on production, all of which are assessed by a PFMEA team using predefined linguistic terms and suggestions. Applied to a case study of a Tier-1 automotive supplier, the FRADAR method effectively ranks failure modes, providing a structured and precise approach for action prioritization. The results highlight the model’s potential to enhance decision-making processes, offering a robust framework for implementing PFMEA recommendations in the automotive industry.