Uncertainty Modelling in Life Cycle Costing Analysis for Rail Level Crossing Systems

Abstract

Asset degradation and maintenance strategies are driving factors that cause the variation in life cycle cost (LCC) of infrastructure assets. In the railway industry, several researchers have analyzed the impact of the uncertainty on LCC, but the emphasis was laid on traditional ballasted tracks. Another type of track structure, embedded rail system (ERS), has not received much attention to date. The research screens the problem to Harmelen level crossing system (LCS), one of the applications of ERS, and proposes a reliability-based LCC model for this type of railway assets, which incorporates the uncertainty associated with rail degradation and maintenance interventions to LCC analysis in order to optimize the maintenance strategies and achieve a cost-effective life cycle management of Harmelen LCS. The model application is demonstrated in Microsoft Excel and partly validated by field data. With the rail failure data, cost information and pre-defined maintenance policies (3 conditions), the model output is able to answer two practical questions for asset managers: ‘when would be the most cost efficient to preventively replace the rails in Harmelen LCS’ and ‘how much money does one asset manager have to save to own the asset in the optimized lifecycle’. Sensitivity analysis is further performed to take more different settings into account and facilitate better understandings about the connections between model outcomes and input variables. Recommendations concerning the model application are provided both for Harmelen LCS and other types of railway assets.