Three-way failure mode and effect analysis approach for reliability management in multigranular unbalanced linguistic contexts

Failure mode and effect analysis (FMEA) is one of the most influential reliability analysis techniques and has been widely used in a variety of fields. Due to differences in knowledge and experiences, the subjective assessment information provided by experts may be multigranular unbalanced linguistic terms. Furthermore, existing FMEA methods built in multi-criteria decision-making paradigm ignore the failure cost of each failure mode under different decision-making actions. Based on three-way decisions with decision-theoretic rough sets, this paper constructs a novel three-way FMEA framework in multi-granular unbalanced linguistic contexts. Firstly, we transform multigranular unbalanced linguistic information into uniform and balanced linguistic information, and propose the 2-tuple probabilistic linguistic term sets to integrate linguistic assessments of all experts. Secondly, an optimization model is designed to determine the weight of risk factors, the TOPSIS method is used to calculate the conditional probability of each failure mode. Thirdly, the concept of failure-loss function matrices has been introduced to derive three-way decision rules of FMEA. Finally, an illustrative reliability management of offshore wind turbine system is used to demonstrate the application and effectiveness of the proposed methodology. The three-way FMEA framework can provide decision makers with targeted reliability management strategies.