Rams-based comprehensive evaluation method for EMU components

Abstract

EMU (Electric Multiple Units) components were evaluated in multiple dimensions, i.e. reliability, availability, maintainability, and safety. A parameter estimation method, which is based on the data on the mileage between failures and quantities monitored in the actual operation, was put forward for the Weibull proportional hazard model to determine their operational reliability. A multi-index component maintainability evaluation model, which is based on empirical distribution functions, and a maintainability cluster evaluation model, which is based on whitened weight functions, were built, and the entropy weight method was introduced to determine the estimates of the indexes. A component safety evaluation method, which has the safety risk factor as its evaluation basis, was built using both the fuzzy theory and the analytic hierarchy process. A RAMS comprehensive evaluation model based on the linear weighted synthesis method was proposed. All of the models and methods are aimed at meeting the needs of this multidimensional component evaluation. This evaluation method was verified using actual gearbox operation parameters. The reliability and availability evaluation curves based on the Weibull proportional hazard model, whose parameters were determined according to the failure data, show that the EMU component reliability and availability decrease as the EMU mileage increases, thus verifying that this evaluation method is reasonable. The calculated EMU gearbox degree of safety is 0.8659, at an excellent level. The evaluated EMU gearbox maintainability is at the moderate level of III. The proposed evaluation method can reflect the relations of the component reliability and availability to the quantities monitored in operation more accurately and more comprehensively and the actual component maintainability and safety levels in a more objective way. It can provide a theoretical basis for managers and design departments to improve and evaluate the performance of the components, determine their maintenance intervals, and develop scientific preventive maintenance strategies in order to reduce their overhaul cost and increase their maintenance efficiency.