What is predictive maintenance?

Instead of waiting for breakdowns or fixed-interval PMs, predictive programs use live sensor data and fault trends to service vehicles only when risk rises. The goal: maximum availability at minimum cost.

Starter stack (what you actually need)

Signals to monitor (first 90 days)

Signal Why it predicts failure Action threshold (example)
High coolant temp / ECT Cooling issues → roadside failures >105°C for 60s → stop & inspect
Oil pressure drop Lubrication problems → engine wear <15 psi at idle → sample oil
Battery voltage Electrical faults → no‑starts <12.2V parked 24h → test battery
Misfire counts Ignition/fuel issues → power loss > 5 events / 100 km → plug/coil check
DPF soot / differential pressure Restricted exhaust → derate risk DP >10 kPa sustained → forced regen
DTC frequency (same code) Recurring fault → escalating risk 3x in 7 days → open work order

Alert → triage → work order (workflow)

30‑60‑90 rollout (starter program)

KPIs that prove it works

💬 FAQs

Most systems buffer video and upload only events or on demand. Continuous recording is configurable by policy.
No—start where value is highest (heavy‑use routes, critical assets). OBD for light vehicles, CAN gateway for heavy equipment.
Track breakdowns, road calls, and parts spend vs baseline; include screenshots and before/after charts in quarterly reviews.
Tip: pair predictive alerts with a parts mini‑kit for each vehicle class (sensors, filters, coils). Faster triage, less downtime.