A Multi-Criteria Decision Framework for Railway Switch Maintenance Prioritization in Urban Rail Systems

This study proposes a multi-criteria decision-making (MCDM) framework for the prioritization of railway switch maintenance in urban rail systems. Railway switches are critical infrastructure components subject to complex operational and structural conditions, making maintenance planning a challenging task. To address this problem, the proposed approach integrates the Analytic Hierarchy Process (AHP) for criteria weighting with TOPSIS and PROMETHEE methods for ranking alternatives. The methodology is applied to real-world data obtained from the urban rail system of Istanbul, Türkiye, including maintenance and failure records of railway switches over the period 2018–2023. Failure frequency is used as a performance indicator to evaluate the consistency of model-based rankings. The results indicate a high level of consistency between model-based and failure-based rankings, with most switches exhibiting only minor ranking deviations across methods. The proposed framework successfully identifies high-priority switches that correspond to those with the highest observed failure frequencies. Observed discrepancies are limited and can be attributed to external operational factors and data limitations. The findings demonstrate that the proposed framework provides a structured and data-informed approach for maintenance prioritization. By integrating multiple criteria with real operational data, the approach offers a practical alternative to conventional time-based maintenance strategies and supports more efficient resource allocation in urban rail systems.