Outranking-based failure mode and effects analysis considering interactions between risk factors and its application to food cold chain management

Failure mode and effects analysis (FMEA) is helpful to control potential risks of enterprises by ranking failure modes based on their evaluation values regarding multiple risk factors. However, due to the cognitive limitation of experts, obtaining explicit evaluation of failure modes is difficult; in addition, existing literature on FMEA rarely considered interactions between risk factors. To bridge these research gaps, this paper proposes an outranking-based hesitant fuzzy linguistic FMEA method. Firstly, inspired by the PROMETHEE-II and the best-worst method, the outranking relation between each failure mode and the best or the worst failure mode is determined, so as to reduce the number of pairwise comparisons. Also, the hesitant fuzzy linguistic term set is used to express the ambiguity of expert judgments regarding the comparisons of failure modes. The Choquet integral is applied to integrate the scores of risk factors considering their interactions. Finally, the proposed method is implemented in an example of food cold chain risk assessment. Results shows that failure modes with high risks are the illness of cold chain workers, product loss and long-time transportation. This study contributes theories about managing ranking efficiency of failure modes in FMEA under fuzzy evaluation environment with interactive risk factors when addressing food cold chain risk evaluation problems.