Metro Vehicle Fault Information Statistical Analysis And Maintenance Strategy Optimization

This article is based on university-enterprise cooperation project--urban rail vehicle maintenance technology research. Its content is to fully research and analyze the metro vehicle equipment maintenance processes, technologies and strategies, that we can develop a set of maintenance systems and process content. Then on the basis of the statistical analysis of the subway vehicle fault information data, we can summarize the distribution of fault. For the existing problems in the maintenance strategy research, combined with enterprise, we can use the analytical methods to optimize the current equipment maintenance strategy.The main contents of this article include:First, the article gathers and organizes information about urban rail transit vehicle maintenance strategy literature and information, including the world’s metro developed countries such as Japan, the United Kingdom, the United States, as well as China’s Hong Kong subway vehicle maintenance strategy. We can compare their strategies and systems overhaul the content and the advantages and disadvantages to analyze Chinese domestic cities metro vehicle maintenance strategy.Secondly, we can fully analyze metro vehicle equipment failure, including equipment failure type, mode, mechanism, failure analysis methods used. On this basis the classification system of the vehicle, the use of Minitab software for critical analysis subsystem failure information data, mapping the fault distribution for predicting subsystem failure to provide evidence and guidance.Finally, for vehicular equipment in the repair process strategies adopted methods, we can use the analytic hierarchy process and fuzzy theory combined method (FAHP) to decision-making. We can build a collection of evaluation indexes, economy, feasibility and effectiveness and segmentation factors, structural maintenance mode decision model, combined with the actual maintenance use, for example analysis of the bogie gearbox maintenance decision-making process, and find the final decision by calculating the optimal use of state of repair for the repair and maintenance strategy. For device-specific parts of the overhaul level, we use the theory of Markov to construct decision model. Door limit switch on the system’s maintenance cycle is determined by using multi-objective fuzzy theory model to solve the optimal maintenance cycle.