Predictive Maintenance AI

Moving from Mileage Intervals to Stress-Based Servicing: The Math Behind Sense

FleetFix AI Research Group·Oct 2026·5 min read· Algorithmic Maintenance
Predictive Fleet Maintenance AI
Multi-dimensional engine stress and thermal degradation telemetry modeling.

Two identical 4-ton diesel delivery trucks can both register 10,000 km on the odometer. But one spent 80% of its hours idling with the AC running in Dubai city traffic, while the other ran long-haul highway routes between Abu Dhabi and Fujairah. Treating both engines identically guarantees unexpected mechanical failure.

Engine oil degradation is primarily a function of fuel-burn volume, cold starts, idle hours, and thermal cycles, not simple odometer distance. High idle ratios create severe fuel dilution and soot loading, breaking down viscosity long before 10,000 km.

The Sense Formula

By ingesting total liters consumed, engine running hours, RPM distributions, and coolant temperature variance, FleetFix Sense dynamically computes remaining fluid life to prevent catastrophic bearing wipe.

1. Early Fault Detection (Beta)

Instead of waiting for an engine check light, telematics anomalies in oil pressure delta and alternator ripple signal component degradation weeks before roadside failure occurs.