Predictive Maintenance and Operations in Railway Systems

The present paper explores the current need of a predictive model for Maintenance and Operations in Railway Systems that tackles the challenges of vertical separation. Railway Vehicles and Track (V-T) systems are responsible for large investment and maintenance costs, which should be optimised using a reliability-based Maintenance and Operation (M&O) decision model. The European railways face vertical separation, adding further complexity to M&O: while Train Operating Companies (TOCs) are maintaining their trains, track maintenance decisions are made by the Infrastructure Manager (IM). However, in this vertically separated system, no clear decision model seems to be in place to optimise the overall life cycle impacts of M&O decisions across the different railway agents. Therefore, a Collaborative Decision Model (CDM) is missing to align predictive M&O decisions. TOCs and IM are monitoring the evolution of their own assets and using sensor systems and signal processing techniques to identify and predict specific failures and support their M&O strategies in separate decision models. These M&O strategies, which very often have conflicting objectives, which may lead to sub-optimal overall life-cycle impacts. In fact, V-T systems have relevant joint behaviour in degradation, which significantly affect wear and damage of wheelsets and rails, as well as the life-cycle costs, reliability, availability and safety of the overall railway system. Thus, misalignments in M&O decisions can be reduced by using cooperative strategies between TOCs and IM. The current project PMO-RAIL will contribute towards an innovative reformulation of railway M&O problems, aiming to achieve a proof-of-concept that such a CDM framework to support PM&O scheduling decisions can provide better overall life-cycle impacts.