Journal of Neutrosophic and Fuzzy Systems (JNFS) Vol. 05, No. 01, PP. 23-29, 2023 DOI: https://doi.org/10.54216/JNFS.050103 Received: August 15, 2022 Accepted: December 19, 2022 23 Integrated Multi-Criteria Decision Making Via Trapezoidal Neutrosophic Sets to Evaluate the Risks of Failure Mode Mahmoud A. Zaher 1 *, Nabil M. Eldakhly 2 1 Faculty of Artificial Intelligence, Data Science department, Egyptian Russian University (ERU), Cairo, Egypt 2 Faculty of Computers and Information, Sadat Academy for Management Sciences, Cairo, Egypt & French University in Cairo, Egypt Email: mahmoud.zaher@eru.edu.eg; nabil.omr@sadatacademy.edu.eg Abstract The purpose of a failure mode and effect analysis (FMEA) is to improve the safety and dependability of a system, product, procedure, or facility by identifying potential points of failure and determining the consequences of such failures. The assessment of failure modes, the weighting of risk factors, and the ranking of failure modes are all areas where the conventional FMEA falls short when put to use in the real world. To assess the hazard of failure modes in a trapezoidal neutrosophic sets environment, this research proposes a model that combines the neutrosophic sets and MCDM technique such as WASPAS. The WASPAS MCDM method is used to calculate the weights of standards and order the alternatives. Advantages of trapezoidal neutrosophic numbers in dealing with uncertainty, ambiguity, and incompleteness are combined with the benefits of WASPAS to create the suggested risk prioritization strategy. Keywords: Failure mode; MCDM; Trapezoidal Neutrosophic Sets; Risk assessment; 1. Introduction To boost the dependability and care of goods, procedures, and services, failure mode and effect analysis (FMEA) is a viewpoint risk analysis method for pinpointing and eradicating probable sources of failure, issue, and mistake. Instead of trying to fix problems after they've already affected customers, FMEA focuses on preventing the most common causes of failure in the first place. Since its inception as a formalized design philosophy in the 1960s, FMEA has been used extensively in the aircraft industry to enhance product quality. Since then, FMEA has evolved into a robust tool utilised by a broad variety of sectors, counting the nuclear, motorised, mechanical, and healthcare sectors, among many others[1]–[3]. Traditional FMEA analyses potential points of failure in terms of three risk factors: how often they are to occur, how severe their consequences, and how likely they are to go unnoticed (D). Failure modes' risk levels are prioritised using hazard numbers (RPNs) derived by multiplying the occurrence, severity, and distribution (OSD) of an event[4], [5]. Despite its usefulness as a screening instrument, the classic FMEA has been heavily criticised in the literature for a number of shortcomings. As a result of the FMEA team members' subjective and nebulous assessments, it is challenging to provide an accurate and comprehensive assessment of the risk variables[6], [7]. The old-style FMEA uses just the three risk variables O, S, and D to evaluate failure modes, which may overlook other crucial aspects of the process or system. This is not a realistic approach because (3) the relative relevance of risk variables is ignored. (4) There is some debate about whether or not RPNs should be used to rank the risks associated with various failure scenarios[8], [9].