Optimization of preventive maintenance schedule of subway train components based on a game model from the perspective of failure risk

With the sustainable development of urban transportation systems, the safety and economy of subway trains have become important criteria. However, in the process of formulating the operation and maintenance strategy of subway trains, there is always a conflict of interest between the operator, who aims to improve the operation reliability, and the maintainer, who aims to reduce the maintenance cost. To resolve this conflict, this paper proposes a preventive maintenance decision-making method for subway train components based on a game model. A failure-rate model based on the memory factor was developed and combined with the dynamic attenuation law of a subway train. The failure risk of subway train components was quantitatively evaluated, and a risk penalty cost model was established. Next, a maintenance cost model based on the maintenance reliability and economy was developed. Then, a non-cooperative dynamic game model with operators and maintainers as players was developed, and the balance was solved using the particle swarm optimization algorithm. Finally, the preventive maintenance of the bogie axle box of a subway train was examined for validation. The validation results indicated that the proposed method can balance the interests of the subway train operation and maintenance departments and improve the operation and maintenance decision-making in the field of sustainable cities.