Case Study: VR Group achieves improved punctuality and fleet reliability with SAS Analytics

VR Group - Customer Case Study

VR Group, Finland’s state-owned passenger railway operator with about 1,500 trains, faced rising maintenance costs and customer frustration from unplanned delays caused by parts failures and inefficient, schedule-based servicing. The company needed to boost punctuality, safety and cost-efficiency while keeping ticket prices competitive.

By fitting trains with sensors and using SAS Analytics to turn IoT data into real-time insights and predictive models, VR Group shifted from reactive to predictive maintenance—anticipating failures (for example, door or wheel issues) and optimizing service intervals. The result is improved fleet reliability and punctuality, lower spare-parts inventory, potentially up to a one-third reduction in some maintenance work, and a better passenger experience with more competitive pricing.

VR Group

Kimmo Soini

Senior Vice President for Maintenance