According to the Office of Rail Regulation, more than one third of the lifecycle costs of rolling stock is spent on maintenance. Maintenance quality, cost, and fleet availability are complementary goals that have to be carefully balanced, keeping in mind national regulations that have to be fulfilled. Modern railway systems pose a great challenge for the fleet maintenance management, as the traditional fleet maintenance optimization schemes with fixed cycles (mileage- or time-based) reach their limits on flexibly managed rail systems. Innovative approaches with data-driven predictive and preventive maintenance optimization are being developed, but are still far from being an industrial standard in an industry that tends to stick with well-proven traditional technology.
One way to evaluate system behaviour and performance is discrete-event simulation (DES), which is already widely deployed in manufacturing and logistics processes. DES provides an alternative to analytic methods (such as Value Stream Mapping or Process Mining) and mathematical optimisation methods (such as linear optimisation or metaheuristics) for evaluating system behaviour and performance.
As a framework for the implementation of the preventive maintenance optimization, the AnyLogic multi-method modelling software was selected. The crucial factor for the choice was the high customizability with Java code and libraries, support for agent-based modelling (ABM) as well as conventional discrete event simulation (DES) and the rich geographic information system (GIS) module.
Read mode about AnyLogic railway simulation capabilities >>
