Experimental Study to Improve the Reliability of a Tramway Air Conditioning System in Ouargla, Southern Algeria, using a Hybrid RPI-RPN-Fuzzy MCDM Methodology to Detect Critical Failure Modes via FMEA Technology

Abstract

The study focuses on analyzing tram air conditioning (AC) maintenance with the goal of enhancing overall reliability and extending the system's lifetime. To improve the design and performance of tram air conditioning maintenance, the FMEA method, which utilizes the Risk Priority Number (RPN), is employed. Limitations such as non-injectivity and non-surjectivity have impacted FMEA. This research introduces an integrated risk assessment model that combines various methodologies to comprehensively evaluate failure modes. The entropy method is utilized to determine the weights of risk variables, followed by integrating failure mode classifications from the RPI, EDAS, VIKOR, and FUZZY TOPSIS models using integrated MCDM techniques. A preference ordering method based on similarity with the optimal solution (TOPSIS) is applied. The effectiveness of the proposed methodologies was verified and the reliability of the system increased by 22.72 % using statistical data and expert opinions for trams in southern Algeria.