Around 100 freight trains each year are abruptly pulled from service for urgent maintenance.
It’s an essential safety measure, but it comes with commercial consequences.
Why does it happen?
Wheel Impact Load Detectors (WILD) gather data from passing trains at over 70 sites across GB rail. If a train is detected with a degraded wheelset, it will trigger an urgent alert. This requires the train to travel at reduced speed and it may have to terminate early.
If this causes considerable network delays, the operator could be subject to significant financial performance penalties. Their customer’s delivery schedule will be disrupted, too.
So what if we could use existing industry data to predict where maintenance is needed, before it causes issues on the network?
Data diagnosis
The WILD project has been running for several years already, ensuring rolling stock is fit for use on a day-to-day basis. In that time, it has also built a sizeable bank of data about wheel damage.
Our Data Insights team is building a tool that harnesses that existing data to accurately predict when a wagon needs maintenance—before the threshold is reached. It's called the Wheelset Intervention Support Tool (WIST).
The bigger picture
From one dashboard, freight operators can see the condition of their whole fleet. Wagons affected by wheel flats, cracks, or diagonal imbalance are easily visible.
The freight operator can schedule damaged wagons in for maintenance well before they’re at risk of triggering a WILD alert.
The new decision-making system was put through its paces in a successful pilot with Freightliner and DB Cargo, in collaboration with the University of Huddersfield.
Paul Long, Head of Track and Rolling Stock Engineering at Freightliner Group Ltd, shared his experience.
‘Using this data has always been an issue and it has required processing and interpretation by experts to enable it to be put to practical use,’ Paul said. 'The creation of the WIST dashboard has been a game-changer. It allows access to live processed data which can be filtered and interrogated by a layman. Within the last week, the WIST tools have been used by Freightliner to identify a wagon with a broken spring which was then removed from service and repaired.’
Get the benefits
From Spring 2026, the finished tool will be made available to the freight sector. Freight operators with radio frequency identification tags fitted to their wagons can request their own personalised dashboard.
Reducing the number of faulty wagons not only improves safety performance and prevents delays and penalties but also contributes to the longevity of the infrastructure. Imperfections in wheelsets can cause faster rail wear.
This predictive data tool is essential for a safer, more efficient, less costly rail freight system. As we progress we will be able to add more features too, so watch this space.