Identifying critical components for railways rolling stock reliability: a case study for Iran.

Electrical railways constitute a vital component of transportation infrastructure worldwide, with rolling stock representing a key element of these systems. Given the extensive operational hours of such systems, effective maintenance scheduling and asset management are imperative to ensure reliability and safety while mitigating costs. This paper addresses the challenge of optimizing maintenance practices for railway rolling stock by introducing a novel implementation of reliability-centered maintenance (RCM) grounded in the reliability block diagram (RBD) framework. This methodology meticulously incorporates reliability parameters into maintenance strategies, aiming to enhance the operational efficiency of railway systems. Leveraging the criticality index, the study identifies components crucial for train reliability, facilitating cost-effective maintenance management. The proposed approach is applied and validated on the Tabriz line 1 metro in Iran, a system with over six years of operational history. Analysis reveals the bogie subsystem's criticality due to its interconnected components, with parts exhibiting significant mean time to repair (MTTR). Conversely, the brake system emerges as the most reliable subsystem. Additionally, sensitivity analysis demonstrates an inverse relationship between repair rates and component sensitivity, highlighting the pivotal role of efficient repair processes in bolstering system reliability. This research contributes a comprehensive and validated methodology for RCM in railway rolling stock, emphasizing cost reduction, system reliability, and strategic prioritization of maintenance efforts. As the approached method in this research is not limited to the specific case study and can be applied in any system by generating the RBD and reliability parameters of the system we want to study The findings hold significant implications for the global planning and execution of railway maintenance operations, setting a new standard for reliability-centered maintenance practices in the field.