Sequential Decision And Dynamic Scheduling Of Maintenance Process For Metro Core Electrical Components

In the context of rapid urbanization,with the increase in the number and age of subways,some subway lines have come to the period of intensive repair and advanced repairs.With the rapid increase in the demand for advanced maintenance,how to improve the maintenance capability and reduce the maintenance cost has become an important issue in the maintenance industry.In recent years,due to the low-cost and high-efficiency advantages of condition-based repair stations,they have been gradually researched and applied in the low-level maintenance of the subway maintenance industry.However,advanced repairs have the characteristics of heavy maintenance tasks,uncertain process routes,and complex process,which require high accuracy of the maintenance process.Simply relying on subjective experience or research on condition-based maintenance in low-level maintenance cannot effectively guarantee the accuracy of the maintenance process plan and resource scheduling plan.It also restricts the application and promotion of condition-based maintenance in advanced maintenance.Therefore,in order to cope with the rapidly increasing number of advanced maintenance tasks,the optimal decision-making of maintenance process sequence and research on dynamic scheduling of maintenance resources is an important way to solve the problem of maintenance capability of enterprises.To sum up,this thesis takes subway electrical components as the research object,and aims to improve the maintenance ability of subway electrical components and reduce maintenance costs.On the basis of analyzing the influence of multiple health states on the overhaul process of electrical components and constructing a research framework,the research focuses on the maintenance process sequence decision in multi-health state and the dynamic maintenance scheduling problem behind it.And the feasibility and effectiveness of the method proposed in this thesis are verified through application cases and simulations.The details are as follows:(1)Taking the maintenance process of subway electrical components as the research object.This thesis summarizes the characteristics of the maintenance process of subway electrical components,and also analyzes the influence of the health status on the maintenance process of electrical components.Based on this,a decision-making and dynamic scheduling framework for the maintenance process sequence of subway electrical components is constructed.(2)In order to improve the accuracy of the state parameters of the maintenance sequence decision under the influence of the health state,the evaluation index and comprehensive evaluation method of the health state of the electrical components are firstly studied;In order to improve the accuracy of decision-making in the maintenance process sequence of subway electrical components,the thesis built a decision-making model for electrical components maintenance process sequence,and based on the D-S evidence theory,the multi-attribute decision-making of the condition-based maintenance of electrical components is proposed and constructed.Finally,the model is validated with a real case.(3)Constructed a dynamic scheduling model based on timing maintenance process sequence decision-making.Combined with rolling horizon procedure,this thesis sets up two event-driven rescheduling mechanisms,including the number of workpieces arriving and the tolerance of process completion time deviation.And a hybrid particle swarm optimization and genetic algorithm is used to solve the dynamic scheduling model.(4)Based on the above research results,taking a subway maintenance enterprise as an example,using Any Logic software for simulation,the proposed method is compared with the actual maintenance workshop and static scheduling simulation results,and the feasibility and effectiveness of the method proposed in this thesis are proved.