<p>A sewage treatment plant (STP) is employed for the removal of toxic pollutants from domestic or municipal sewage, thereby producing an effluent that can be easily discharged into the environment. Several failure modes (FMs) associated with the STP may lead to its failure. Identification of the critical FMs, from among several FMs, and devising effective strategies to either eliminate or minimise their occurrence are crucial for the nonstop functioning of the plant. Failure mode and effects analysis (FMEA) is a commonly used technique for ranking the FMs of any equipment or system. In general, FMs in FMEA are evaluated and ranked based on the risk priority number, which is calculated by multiplying the associated risk factors, i.e., occurrence, severity, and detection. In recent times, the fuzzy- based multi criteria decision making (FMCDM) approach for FMEA has been effectively used for the evaluation of potential FMs. However, the rank assigned to different FMs by different FMCDM methods might be different. Consequently, this study proposes a robust hybrid fuzzy MCDM-based FMEA approach where two FMCDM methods, i.e., fuzzy analytical hierarchy process (FAHP) and fuzzy proximity index value (FPIV), are used to produce a reliable rank of the FMs. Fifteen possible FMs of STP are identified through experts’ consensus and subsequently ranked using the FAHP and FPIV methods. Sensitivity analysis is employed to establish the robustness of the ranking results produced by FAHP and FPIV techniques.</p>