Human Reliability Analysis of Aircraft Landing Operation Using an Integrated Group Consensus‐Based Approach Under Double Hierarchy Hesitant Fuzzy Linguistic Environment

Aircraft landing operation is one of the most crucial and risky procedures during a flight, and various human‐related failure modes may affect its safety. Recent studies on human reliability analysis (HRA) have demonstrated the value of using expert knowledge to assess potential human errors. Focusing on human‐error assessment during aircraft landing operations, this study proposes an HRA framework based on failure mode and effects analysis (FMEA) by integrating double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs), a group‐consensus mechanism, data envelopment analysis (DEA), and evaluation based on distance from average solution (EDAS). First, DHHFLTSs are used to express the uncertain and hesitant risk‐factor evaluations provided by experts, while interval 2‐tuples support the subsequent aggregation and computation. Then, the group‐consensus mechanism is incorporated into the HRA process to determine expert weights by considering peer‐assessed credibility and agreement with the group. Next, the DEA model is employed to calculate the weights of different risk factors according to their orientations. Subsequently, the EDAS method is used to calculate relative appraisal scores and rank the potential human‐related failure modes. Finally, an illustrative case of aircraft landing operation is investigated to demonstrate the applicability and feasibility of the proposed method. The results show that the proposed method can represent uncertain linguistic evaluations, determine expert and risk‐factor weights, and provide a relative prioritization of human‐related failure modes. The resulting appraisal scores are relative risk‐priority indices rather than calibrated human error probabilities or measured improvements in operational reliability.