A Hybrid FMEA–Stochastic Modeling Approach for Sustainability Evaluation in Remanufacturing Using the MABAC Method

Remanufacturing has emerged as a cornerstone of sustainable production and circular economy strategies, yet its complex risk and performance factors demand robust assessment tools. This research proposes a hybrid framework combining Failure Mode and Effects Analysis (FMEA), stochastic modelling, and the MABAC (Multi-Attributive Border Approximation area Comparison) method to evaluate remanufacturing alternatives. The study employs simulated data to represent diverse sustainability scenarios, incorporating uncertainty through probabilistic weighting of risk factors. The FMEA component enables systematic identification of failure modes across environmental, economic, and operational dimensions. Stochastic modelling enhances this by capturing variability in expert judgment, while the MABAC method ranks alternative strategies based on multiple sustainability criteria. The results offer practical insights into which remanufacturing pathways provide optimal performance under uncertain conditions. This hybrid approach advances the decision-making toolkit for sustainable manufacturing by integrating qualitative and quantitative inputs within a transparent, adaptable model. The framework holds potential for application in real-world remanufacturing settings, particularly where decision complexity and uncertainty are high. This study contributes to the literature on sustainable systems engineering by offering a replicable model that bridges risk analysis and multi-criteria decision-making in remanufacturing.