optimizing maintenance and repair in a railway transportation company in southern iran: a system dynamics modeling approach

This study develops and evaluates a system dynamics (sd) model to optimize maintenance and repair processes for a railway transportation company in southern iran. recognizing the intricate feedback relationships among workforce skill, part quality, maintenance budget, failure rate, mean time between failures (mtbf), and mean time to repair (mttr), the proposed model was constructed using operational data and expert insights, and implemented in vensim. five managerial scenarios were simulated to assess the impact of human, technical, and managerial policies on key performance indicators, including fleet availability, downtime costs, and rework rates. the simulation results reveal that traditional reactive maintenance approaches are inadequate to manage the system's complexity, resulting in higher failure rates, operational delays, and indirect costs. in contrast, preventive and integrated maintenance strategies—which simultaneously address human and technical factors—achieved substantial performance improvements. among the scenarios, the integrated policy that combined workforce training with part-quality enhancement produced the most significant results, increasing fleet availability and reducing overall system costs. conversely, short-term budget cuts, while appearing economical, led to long-term inefficiencies and reduced reliability. the study concludes by recommending continuous workforce development, comprehensive preventive maintenance, dynamic budget allocation, optimized spare-part inventory management, and a transition toward data-driven intelligent maintenance as critical policies to achieve operational and economic sustainability in railway systems.