Sustainable Lifecycle Management of Urban Rail Rolling Stock: A Data-Driven Approach to Optimal Replacement Timing

This study investigates the optimal service life of urban Electric Multiple Units (EMUs) by integrating two complementary evaluation methods: economic service life and maintenance limit life. Using a comprehensive dataset from Seoul Metro—including 498 trainsets and 3554 overhaul records—this research examines the relationship between long-term maintenance costs, depreciation, and residual values. The economic service life is derived by minimizing the average equivalent annual cost (AEC), while maintenance limit life is assessed based on government guidelines that define cost-inefficiency thresholds. The analysis finds that the average economic service life for EMUs on Lines 1–4 is approximately 39 years—substantially exceeding the traditional 25-year benchmark used in past replacement policies. Maintenance limit life, based on permissible cost ratio thresholds, extends up to 47 years in some cases. Sensitivity analysis indicates that maintenance cost variations exert a greater influence on optimal service life than discount rate assumptions, highlighting the importance of strategic maintenance management. The proposed dual-framework approach demonstrates the limitations of rigid, statutory-based replacement planning and supports a transition toward data-driven, line-specific decision-making. The findings provide actionable insights for transit authorities and policymakers seeking to improve capital investment efficiency and optimize lifecycle management of urban rail assets. Beyond economic efficiency, the study contributes to sustainability by supporting resource-efficient asset utilization, reducing premature disposal of serviceable rolling stock, and lowering lifecycle carbon emissions associated with manufacturing new vehicles. The proposed framework thus offers a practical basis for integrating economic and environmental considerations in sustainable urban rail asset management.