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.

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

BAGLIETTO, EMANUELA;Consilvio, Alice;Febbraro, Angela Di;Sacco, Nicola
2018-01-01

Abstract

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.
2018
978-1-5386-7528-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/940273
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