How Arriva cut operating costs with predictive maintenance

By planning maintenance around predicted faults, Arriva’s Prague-region operation reduced towing interventions, required fewer spare buses and lowered its net cost per kilometer.

About Arriva

Arriva is one of Europe’s largest transport companies. It employs around 35,000 people across 11 countries and provides 1.5 billion passenger journeys a year, operating around 2,000 buses in Czechia. 

The challenge

When maintenance teams cannot see the condition of a vehicle’s components, they have to rely on service intervals, visual inspections and manual diagnosis. Parts may be replaced too early or too late, while unexpected faults create urgent work for the depot.

For a contracted bus service, the impact quickly reaches the network. A breakdown can take a bus out of service, require a spare vehicle and disrupt the timetable.

The approach

Arriva deployed Stratio’s fleet reliability intelligence platform to identify and diagnose developing faults. Its Diagnostic AI analyzes vehicle data and gives the workshop advance warning of likely failures.

This allows the team to investigate issues and plan maintenance before a breakdown occurs. Arriva measured the program against operational and financial outcomes, including productive kilometers, spare-fleet requirements and towing interventions.

“By using the Stratio Platform we are able to discover a possible failure before it occurs, plan our maintenance and use our fleet more effectively. The Stratio solution is indispensable because it allows for the planning and scheduling of actions to create additional competitive advantages.”

Radovan Ředina

Project Manager, Arriva

Fewer spare buses and towing interventions

With earlier warning of component problems, the maintenance team can group work into quieter periods and keep more buses available for service. Arriva reduced its spare-fleet requirement by 25%, returning vehicles to productive use. The same approach reduced towing interventions by 66.6%. Fewer buses failed on the road and needed to be recovered to the workshop.

Lower costs and more planned work

Predictive insights help the team replace parts when required and move work from emergency repair to planned maintenance. Mean time between failures increased by 13.5%, while the ratio of planned to unplanned maintenance improved by 33.3%. After project costs, Arriva recorded a 2% net saving per kilometer operated. This reflects the measure used in the service contract: cost per productive kilometer rather than maintenance cost per bus.

“We adopted Stratio in 2020 to test whether failure prediction was real. The results speak for themselves: cost per km decreased, time between failures went up, and what began as a pilot in the Prague region is now a standard we keep expanding.”

Daniel Adamka

Managing Director,Arriva CZ