Gareth Tucker

The railway industry forecasts growth in passenger and freight traffic over the next 30 years. This places additional demands on rolling stock depot facilities, many of which were designed and built before the modern age of information technology. This paper explores the potential of improving the efficiency and effectiveness of rolling stock maintenance management to meet the challenges of the near future, by utilising advanced computing techniques. The objective of the work is to create optimised maintenance plans for a fleet of trains, considering optimal use of resources. As a “glue” for joining up functions and operations, a generic Depot and Vehicle ontology (called the Virtual Depot) is introduced. The ontology captures the structures, relationships, and attributes of objects in the Depot (rolling stock, sensors, depot assets, tools, resources, and staff). The ontology is populated with example company and fleet-specific knowledge using an automated knowledge acquisition method. This paper describes the systematic method for the creation of a Virtual Depot. Two particular aspects are discussed in detail—knowledge acquisition of fleet-specific information obtained from a manufacturer’s Vehicle Maintenance Instruction manuals and the construction of a short-term scheduling process within the Virtual Depot. Our evaluation considers the integrative aspects of the method, demonstrating how the ontological structure and its acquired specific information informs and benefits the scheduling process, in particular with respect to schedule optimisation. Results from an initial case study show there is significant potential to optimise short-term maintenance schedules, and the ability to automatically consider resource availability in short-term scheduling is demonstrated.

This paper investigates whether it is possible to develop a wheel profile design that will extend wheelset life compared to an existing commonly used Great Britain passenger wheel profile, the P8. The P8 wheel profile was originally developed in the late 1960s as an alternative to a 1:20 coned wheel profile (the P1). The P1 often required frequent turning as the conicity could increase quickly over time as the wheel wore in service. The P8 was designed based on an average worn shape of a P1 wheel. The P8 was found to stay closer to its original shape as it wore in service. However, new P8 wheels or newly profiled P8 wheels tend to experience a high initial flange wear rate in the first 20,000–30,000 miles, until the worn wheel shape reaches ‘dimensional stability’; after this, the flange width typically remains relatively constant. A ‘Reduced Flange Wear’ (RFW) wheel profile has been developed, based on the P8 profile but with a modified flange root geometry. The Wheel Profile Damage Model has been used to calculate how the proposed RFW wheel profile could reduce wear rates and therefore increase wheelset life. This paper presents results for a typical electric multiple unit train (EMU1) running on rural and suburban routes and a higher speed variant (EMU2) running on an inter-city route. The effect of the proposed RFW profile on rail rolling contact fatigue (RCF) has also been evaluated using the Whole Life Rail Model, for the same routes. The results suggest that the proposed RFW profile does reduce flange wear compared to a P8, with larger reductions achieved on routes that are more curvaceous. For wheel turning based purely on restoring wheel profile geometry, the RFW profile could half the amount of material removed at each turning (based on turning wheels at 250,000 miles). Furthermore, the results show that the RFW profile experiences slightly less wheel RCF damage than the P8. When new, the RFW profile appears to cause slightly higher rail RCF than a new P8 (For radii 700 m < R < 1300 m); however, the results suggest that worn RFW profiles cause very similar rail RCF to that caused by worn P8 wheels.