An Enhanced Failure Mode and Effects Analysis Risk Identification Method Based on Uncertainty and Fuzziness

To address the challenges in traditional Failure Mode and Effects Analysis (FMEA) related to determining factor weights, identifying risk priority of failure modes, and managing uncertainties in the risk assessment process, this paper proposes an enhanced FMEA risk factor evaluation method. This method integrates incomplete and imprecise expert assessments using a fuzzy multi-criteria compromise ranking technique called the "V1seKriterijumska Optimizacija I Kompromisno Resenje" (VIKOR). By employing Fuzzy Evidence Reasoning (FER), the risk factor ratings are represented using fuzzy belief structures to capture their diversity and uncertainty. Objective weights are adjusted using Shannon entropy to correct subjective weights, and the VIKOR technique is applied to prioritize failure modes based on the principles of minimizing individual regret and maximizing group utility. The improved model is applied to identify key equipment associated with oil and gas leakage risk in the Floating Production Storage and Offloading (FPSO) system. Validity and sensitivity analysis confirm the robustness and reliability of the method, enhancing the accuracy and credibility of the evaluation results.