Presentation of the Europe’s Rail LOCATE Project results at WCRR on 8 June 2022
The freight industry is under increasing pressure to reduce costs and improve the reliability of its services. Therefore, the development of intelligent tools and methods for predictive maintenance are needed to optimise the availability of rolling stock, improve the quality of service, and reduce maintenance costs. The framework developed during the LOCATE project aims to address some of these challenges by improving the conditional maintenance of a locomotive bogie (and associated components/subsystems), as one of the main drivers for current maintenance costs of a locomotive is avoiding unnecessary maintenance actions by using predictive maintenance. Several technical challenges also exist which the project has had to address, these include: development of the predictive condition-based maintenance (CBM) framework; statistical degradation modelling of critical failure mechanisms associated with the main components of the locomotive bogie and estimation of hazard rates; development of a mixed-Integer Linear Programming (MILP) approach to tackle the maintenance scheduling problem; development of ‘digital twins’ for appropriate bogie components; specification of a monitoring system with the capability of providing the necessary information to detect changes in component performance and implementing a CBM framework on an aging fleet of freight locomotives.
Full paper can be downloaded at:
This project has received funding from the Shift2Rail JU under the European Union’s Horizon 2020 research and innovation programme, under Grant Agreement 881805.