Modeling and Decision Optimization of Opportunistic Maintenance Strategy for EMU Components Considering RAMS

ABSTRACT

The operation of high‐speed EMU (Electric Multiple Units) systems is usually challenged by high maintenance cost and low maintenance efficiency associated with frequent system shutdowns for maintaining components. By considering reliability, availability, maintainability and safety (RAMS), a cost‐minimizing preventive maintenance decision model based on Weibull distribution is developed for key EMU components. Using reliability and availability factors as constraints, maintainability loss cost and safety risk cost are quantified through a combination of intuitionistic fuzzy set (IFS) and analytic hierarchy process (AHP). A multi‐component opportunistic maintenance strategy is generated by performing particle swarm optimization (PSO) and integrating the opportunistic maintenance plans of components that fall within the opportunistic maintenance mileage window. The results show that compared to traditional preventive strategy, opportunistic maintenance strategy reduces total maintenance cost by 32.4% and number of shutdowns by 19. This verifies that our RAMS‐based multi‐component preventive opportunistic maintenance strategy is both effective and cost‐efficient, offering meaningful references for optimizing the maintenance strategy of EMU components.