Reliability-based advanced maintenance modelling to enhance rolling stock manufacturers’ objectives

Abstract

The light rail is gaining relevance within cities’ transportation networks due to its adequate balance among sustainability, economic and safety factors. Nevertheless, there is still a gap for improvement in those factors through the optimisation of rolling stock maintenance strategies. The development of new and more flexible maintenance strategies at proper indenture levels will aid to improve the reliability and availability of the light rail during the operation phase, as well as to reduce its life cycle cost. Accordingly, the present research develops a multi-objective maintenance model that adopts a novel reliability-based advanced maintenance policy; whose aim is to consistently evaluate short-term information to enhance both traditional maintenance and organisational key performance indicators. The proposed multi-objective mathematical model is solved through a simulation-based optimisation (SBO), which by means of iteration evaluates different maintenance strategies according to the non-dominated sorting genetic algorithm (NSGA II). Empirical results, based on real data obtained from a light rail fleet operating in Spain, demonstrate that the proposed maintenance model for the rolling stock can significantly improve the light rail performance regarding both maintenance and organisational objectives.