As a safety and reliability analysis technique, failure mode and effects analysis (FMEA) has been used extensively in several industries for the identification and elimination of known and potential failures. However, some shortcomings associated with the FMEA method have limited its applicability. This study aims at presenting a comprehensive FMEA model that could efficiently handle the preference interdependence and psychological behavior of experts in the process of failure modes ranking. In this model, a linguistic variable expressed by the interval-valued Pythagorean fuzzy number (IVPFN) is utilized by experts to provide preference information with regard to failure modes’ evaluation and risk factors’ weight. Then, to depict the interdependent relationships between experts’ preferences, the Bonferroni mean operator is extended to IVPFN to aggregate the experts’ preference. Subsequently, an extended TODIM approach in which the dominance degree of failure modes is calculated by grey relational analysis is utilized to determine the risk priority of failure modes. Finally, a practical example concerning the risk assessment of a nuclear reheat valve system is provided to demonstrate the effectiveness and feasibility of the presented method. In addition, a sensitivity analysis and comparison analysis are conducted, and the results show that the preference interdependence and psychological behavior of experts have an important effect on the risk priority of failure modes.

Green supplier selection, as a core part of green supply chain management, has attracted the attention of various researchers in the past decade. Plenty of green supplier selection methods based on multi-criteria group decision-making have been presented in previous literature. However, these approaches ignore the consensus level between the experts, and they rarely consider the priority level among the experts and the interdependent relationship between criteria. To handle these issues, an integrated framework of green supplier selection under the hesitant fuzzy linguistic (HFL) environment was established. In this framework, the preference information expressed by HFL was transformed into the hesitant 2-tuple linguistic (H2TL). Then, the consensus process was introduced into the green supplier selection process to increase the consensus level between experts. The H2TL prioritized operator and Choquet integral operator were respectively applied to construct the group decision matrix and derive the ranking order of green suppliers. Finally, we used a numerical example to demonstrate the validity and applicability of the presented framework and implemented a comparative analysis to highlight the features of the presented method.