A Monte Carlo Simulation Methodology for Uncertainty Analysis in Product Recall Management

Product recall campaigns are performed when defective or unsafe products are in the market or another supply chain stage. Product recall management is an uncertain issue for estimating the operations or processes that cause product failure. It is necessary to use quality engineering techniques and tools for analyzing uncertainty in product recall management. Therefore, we propose a Monte Carlo Simulation for Uncertainty Analysis in Product Recall (MCS-UAPR) methodology to improve decision-making in product recall management. It was applied in a company in the automotive sector and made it possible to identify the operations with the highest impact on the total unit recall cost.