Improved Failure Mode and Effect Analysis Method for Resilience-Based Prioritization in Highway Operation and Management Systems

Abstract Highway operation and maintenance (O&M) systems are increasingly exposed to complex and evolving risks that challenge their resilience and reliability. Traditional risk-based approaches often focus on postevent analysis and cannot address uncertainty across different resilience stages. This study proposes a resilience-based prioritization framework to extend failure mode and effect analysis for highway O&M systems. Expert judgments on resilience failure modes (FMs) across the absorption, resistance, recovery, and adaptation stages are expressed using linguistic Z -number interval rough clouds, capturing uncertainty and randomness. These assessments are integrated using an interval rough cloud hybrid average operator to ensure ordered aggregation. A combined cloud-based CRITIC and fuzzy analytic hierarchy process (AHP) method is then applied to optimize the balance between subjective and objective weights. The extended MULTIMOORA method with an improved Borda rule is used to rank the FMs. A case study of the ShenHai Highway in China further demonstrates that accident control and evacuation during the resistance and recovery stages constitute critical sources of system resilience. Sensitivity analysis indicates that variations in relaxation operators and weight ratio coefficients influence midlevel rankings while preserving the overall prioritization trends. The proposed framework improves the robustness and interpretability of failure mode prioritization and provides a structured tool for supporting proactive decision-making in highway O&M systems under uncertainty.