Predictive maintenance is the approach that uses vehicle data to predict failures before they happen, intervening at the right moment. It relies on continuous analysis of parameters (engine, battery, wear) to estimate when a component is about to fail.
The three approaches compared
- Corrective: repair after the failure (unplanned downtime, high cost).
- Preventive: act at fixed intervals (km or time), even when unnecessary.
- Predictive: act based on the real condition, detected from telematics data — neither too early nor too late.
Why it matters for fleets
Anticipating failures reduces unplanned downtime, extends component life and lowers total cost. On EVs, it also applies to battery State of Health (SoH). It’s one of the frontiers of next-generation telematics — see beyond GPS.
FAQ
What’s the difference between preventive and predictive maintenance?
Preventive follows fixed intervals (every so many km or months); predictive is based on the component’s real condition detected from data, acting only when genuinely needed.
What do you need for predictive maintenance?
Continuous data from the vehicle (telematics), a history to identify failure patterns, and a system that turns the signals into actionable alerts.