AI Technology to Improve Rail Freight Wheelset Maintenance

Wedoany.com Report-Nov 27, The tool will use predictive analytics to monitor the condition of wheelsets, enabling operators to address any potential faults before they lead to costly disruption or safety risks.

The Rail Safety and Standards Board (RSSB) has launched an AI-powered tool to help rail freight operators manage wheelset maintenance more effectively, reducing the risk of derailment and costly disruption. The Wheelset Intervention Support Tool (WIST) uses predictive analytics to identify potential wheelset problems before they escalate. It provides a proactive approach to safety and maintenance.

At present, around 100 freight trains are taken out of service each year for urgent maintenance of the wagons, often related to the poor condition of the wheelsets. These defects not only increase track wear but also drive up infrastructure repair costs. By analysing data from wheel impact load detectors and other sources to monitor wheelset degradation in real time, the RSSB's tool aims to mitigate these challenges.

Key benefits of the WIST include:

Enhanced Safety: Early detection of wheelset failures reduces risks of damage to railway infrastructure and potential safety incidents.

Operational Efficiency: Optimized maintenance schedules minimize downtime and improve service reliability.

Cost Savings: Proactive maintenance lowers the total life cycle cost of wheelsets and reduces the cost of emergency repairs.

To refine the tool based on user feedback, RSSB has launched a pilot programme with selected freight operators. A full release, offering the industry a new way to address longstanding freight car maintenance issues, is expected next year.