# Subway Station Capacity Maintained by Optimizing a Maintenance Schedule of Key Equipment
## 1 Introduction
The only research achievement has been to classify the common equipment faults and find out the fault causes. Gates and escalators belong to electromechanical equipment, and the methods to analyze their reliability are divided into the statistical model and the mechanism model. In this paper, the statistical model is used to analyze the reliability of equipment. Since there is no literature focusing on the reliability of station equipment, the idea of the reliability research on high-speed train bogie system is employed to analyze the reliability of key station equipment. In references [16; 17; 18], the fault data of the bogie system is collected and the reliability of the bogie is analyzed based on the statistical method. In reference [19], each component of the bogie system is estimated based on maximum likelihood estimation and the optimal distribution is determined by the A-D test method. There are many other works on the reliability analysis of mechanical equipment. Not all of the references used are listed here. With regard to the maintenance schedule optimization, the methods of the preventive maintenance schedule model are systematically introduced and the reliability constraints are added to the preventive maintenance schedule model in reference [20]. In reference [21], life distribution of key train operation equipment is determined by the statistical method, and the optimization model of maintenance schedule is established. In reference [22], the operation and maintenance status transition diagram of the whole service life of the equipment is given, and the relationship model between the maintenance schedule and the average availability of the equipment during the whole service life is established. Based on reliability analysis of the key components of rail transit vehicles, the optimization model of the vehicle maintenance schedule is established with the minimum maintenance cost as the goal in reference [23]. This research provided useful maintenance schedule optimization models, but these models take the entire equipment as the research object which lacks pertinence, especially for electromechanical equipment since the failure rate of each component varies greatly. Therefore, it is necessary to build a maintenance schedule optimization model for the components of electromechanical equipment. This paper aims at keeping or even enhancing SSC in the full life cycle. To investigate this issue, the dynamic SSC (DSSC) is defined and the method to calculate the expected DSSC (also referred to as expected station capacity) with equipment failure is proposed in the first stage. The average travel time of passengers is considered as the evaluation indicator of DSSC, which is calculated by passenger simulation model based on AnyLogic (see references [13; 14; 15]). The DSSC model with key equipment failure is established based on binomial distribution and mathematical expectation. In the second stage,the reliability of key equipment at a subway station is investigated, and the lower bound of equipment reliability is determined by sensitivity analysis based on the equipment reliability-expected station capacity curve. In addition, the maximum likelihood estimation method (MLE) is adopted to estimate fault distribution parameters of key equipment, and the Anderson-Darling statistic is used to select the optimal distribution. Finally, an optimization method for the key equipment maintenance schedule is presented in the third stage, which aims at ensuring the reliable operation of equipment with the lowest maintenance cost so that the subway station capacity can be retained in the full life cycle. The main contributions of the paper are as follows:  
1. The interaction between equipment failures and DSSC is analyzed, and the uncertain equipment failure model is incorporated into the DSSC model. 2. Based on the sensitive analysis between equipment reliability and DSSC, a maintenance schedule optimization model of equipment which minimizes the maintenance cost is proposed. This paper is organized as follows.