Reliability analysis of subway door systems based on dual-distribution Monte Carlo simulation

Metro train door systems experience a higher failure rate compared to other subsystems, and their reliability has a direct impact on operational efficiency and service quality. Consequently, it is critical to conduct state assessments of these systems to accurately determine their service conditions. A dual-distribution Monte Carlo simulation method is proposed, which considers component failure rates following exponential distributions and mean repair times following normal distributions. This method develops a reliability simulation model for metro door systems, enabling simulations that span from individual components to the entire system. Utilizing six years of operational data (2018-2024) from a metro operator, the simulation analysis provides reliability indicators for the door system. Comparative verification with the GO analytical method reveals that the reliability indicators obtained through the dual-distribution Monte Carlo simulation exhibit only a 0.95% relative error compared to the GO method results, demonstrating the accuracy of the model. This approach overcomes the limitations of the GO method when dealing with small-sample or uncertain data scenarios.