Design and Implementation of Reliability-Centered Maglev Train Maintenance Management Information System

Abstract

With the rapid development of maglev transportation technology, maglev trains have entered the commercial operation stage worldwide. At present, the maintenance of maglev trains is shifting from traditional planned maintenance to preventive maintenance. It is necessary to study how to scientifically and efficiently achieve the maintenance of maglev vehicle equipment to ensure the safe and reliable operation of maglev trains and improve economic benefits. This article aims to establish a scientific magnetic levitation train maintenance management information system using a Reliability-Centered Maintenance (RCM) strategy, which balances both economy and practicality. Firstly, based on Failure Mode and Effects Analysis (FMECA), an RCM logical decision-making method is proposed for identifying reasonable maintenance modes. By categorizing failure levels to assess their impact, an optimized maintenance strategy for magnetic levitation trains is proposed. By establishing an economic benefit evaluation model and considering the characteristics of remote maintenance and RCM analysis data requirements for magnetic levitation trains, a data warehouse is used as the basic tool for data storage, sharing, analysis, and application. The constructed remote maintenance data warehouse system for magnetic levitation trains can realize functions such as monitoring data query, visualization, and real-time warning of service status, providing decision-making references for the maintenance of the magnetic levitation train system.