Adaptation of the rolling stock technical maintenance system to operating conditions based on risk assessment

Abstract

The operating conditions of railway rolling stock require the implementation of reliable, cost-effective, and risk-oriented maintenance systems (MS). Traditional time- or schedule-based maintenance approaches do not adequately account for the variability of operating conditions and the actual technical condition of components, which often leads to premature or, conversely, delayed repairs. Under these circumstances, the transition to adaptive maintenance systems capable of utilizing predictive models and big data analytics becomes increasingly relevant. An important foundation for such an approach is provided by international standards on risk management and RAMS, which define general requirements for the reliability and safety of railway systems, namely EN 50126-1:2017 and ISO 31000:2018.