Entropy-based borda extended weighted expert FMEA approach: Comparison with classical and fuzzy FMEA on a ship system

In high-risk and safety-critical domains such as maritime engineering, accurate identification and prioritization of failure modes are essential for ensuring system reliability. While classical Failure Modes and Effects Analysis (FMEA) is widely applied, its reliance on averaging expert scores often leads to information loss. Fuzzy FMEA addresses uncertainty but still aggregates data, resulting in similar limitations and added complexity through subjective membership functions and rule structures. This study presents an integrated expert-based risk assessment framework that combines entropy weighting and Borda count aggregation to enhance transparency and preserve expert diversity within the FMEA process. Applied to a marine compressor system comprising 33 failure modes and evaluated by multiple experts, the model individually processes O, S, and D scores, calculates entropy-based criterion weights, and generates consensus Rankings through Borda-based synthesis. Key findings reveal a significant reordering of critical risks with continuously operating compressor, low intercooler pressure, and high intercooler pressure emerging as top priorities. Correlation analysis reveals strong consistency with traditional models (r = 0.973 with FMEA and r = 0.883 with fuzzy FMEA), while providing enhanced diagnostic granularity and operational relevance. The integrated WE-RANK framework provides a transparent, objective, and computationally efficient structure adapted to maritime applications, demonstrating the value of combining established decision tools for expert-based risk evaluation.