Railway system is a typical large-scale complex system with interconnected sub-systems, each containing several components. In this framework, cost-effective asset management and innovative smart maintenance strategies require an accurate estimation of the reliability at different levels, according to the system configuration. Moreover, in order to apply risk-based maintenance approaches, techniques for the evaluation of assets criticality, that take into account the causal-effect relation between system components, are necessary. This paper presents a Bayesian Network modeling approach for the reliability evaluation of a complex rail system, which is applied to a real world case study consisting of a railway signaling system, with the aim of showing the usefulness of the approach in achieving a good understanding of the behavior of such a complex system.


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    Title :

    A Bayesian Network approach for the reliability analysis of complex railway systems


    Contributors:


    Publication date :

    2018-12-01


    Size :

    197394 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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