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Rail wear is the most common defect that affects sharply curved metro rails, thus impacting their renewal periods. This article presents a stochastic model, based on a Weibull distribution, for the estimation of the renewal periods of sharply curved metro rails based on the analysis of the characteristics of rail wear. The model considers several heterogeneous factors to determine their effects on the deterioration process and is shown to be able to estimate the life expectancy of these rails in any wear state, as well as their remaining lives and renewal periods, with respect to these heterogeneous factors. The model is validated by a case study of the Beijing Metro, based on 10 years of rail wear inspection data and heterogeneous factor data of 200 sharp curves.

Because steel rail is one of the most fundamental components of railway operations, the accurate estimation of residual rail service life is of great significance in ensuring the safe operation of railways. In addition, maintenance expenses must be minimized in a manner that allows limited railroad resources to be optimally allotted. In this study, the typical types of continuous rail segments on a rail line are classified into non-sharply curved rail segments and sharply curved rail segments. Using these classifications, a model for estimating the residual service lives of rail segments using a discrete-state conditional probability method is proposed based on an analysis of rail deterioration characteristics. The model considers several heterogeneous factors to determine their influence on the deterioration process and is shown to be capable of estimating the residual service lives of rail segments. Finally, the model is validated through a case study of the Beijing Metro, using inspection records of rail defects in conjunction with heterogeneous factor data to predict the service life of the rail, which is then compared with its actual service life. The model is found to show good agreement with the rail inspection and maintenance records of the Beijing Metro, indicating its appropriateness for use by railroad management in allocating future rail maintenance resources.

Decision-making surrounding asset renewal is essential for the efficient use of renewal resources and safe operation of urban rail transit. In this study, major problems in the current management of urban rail industries in countries with the same problems as those in China were analysed, and in response, a renewal management framework based on service life estimation was proposed to provide adequate decision-making support for urban rail transit assets. In this framework, the cumulative failure frequency of an asset is used to indicate its health condition, and considering the uncertainties and heterogeneities in the deterioration process of assets, a Poisson–Weibull process model-based methodology was developed to estimate the service and residual lives of each asset, which are then employed in analysing its renewal demand and renewal period. Finally, the model is validated through an empirical study of rail renewal in the Beijing Metro. Our evaluation demonstrates that the proposed framework can estimate each asset’s service life accurately and can be used by asset management personnel to establish reasonable renewal plans and provide decision-making support for a scientifically informed resource allocation, thus mitigating major problems in current management practices.

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