Case Study: Ford predicts vehicle failures in advance with Kortical

Predict auto failures in advance using connected vehicle data in real time

Ford partnered with Kortical to tackle predictive maintenance for its connected commercial vehicles. The challenge was to identify imminent equipment failures before they caused breakdowns, reducing costly downtime for Ford Transit fleets and improving service planning for dealers and customers.

Kortical built and deployed a machine learning predictive maintenance model on its AI Cloud platform using connected vehicle modem data, DTCs, and vehicle metadata. The solution predicted 22% of failures an average of 10 days in advance with a 2.5% false positive rate, helping Ford save an estimated 122,000 hours of downtime and around $7 million in potential upside.

Ford