Interval-Valued Fuzzy Fault Tree Analysis Based on BW-ISAM and Its Application in Marine Operation
Authors :- Singh K.; Khungla H.; Kumar M.
Publication :- New Mathematics and Natural Computation, World Scientific, 2025
This paper presents an interval-valued fuzzy fault tree analysis (IVFFTA) for evaluating the system failure probability and identifying the root causes of system failure through qualitative data processing. We utilize triangular and trapezoidal-shaped interval-valued fuzzy numbers (IVFNs) to quantify the qualitative linguistic data. In aggregation methods, assigning appropriate weights to experts is very important as it ensures that their opinions are accurately represented and factored into the overall evaluation. Therefore, this study also develops an aggregation approach, called “BW-ISAM”, by integrating the best–worst method (BWM) with the improved similarity aggregation method (ISAM) to aggregate the interval-valued fuzzy opinions of experts regarding the possibilities of basic events (BEs) in the IVFFTA of a system. The proposed IVFFTA approach utilizes IVFNs to better represent uncertainty and BWM to enhance the consistency of weight calculation in aggregation. We use the Fussell–Vesely importance (FVI) measure to prioritize and rank BEs based on their impact on the occurrence of the top event (TE). To demonstrate the effectiveness of the proposed methodology, we apply this approach to a case study on “loss of ship steering ability”. The results obtained are compared with those from existing approaches for verification.