Predictive Maintenance

Using live condition data — vibration, temperature, current — to predict failures and service equipment just before it would break, not on a fixed calendar.

Definition

Predictive maintenance (PdM) uses real-time condition data to forecast when an asset is likely to fail, so work is performed just in time — late enough to get full life out of components, early enough to avoid the breakdown. Instead of a calendar telling you to act, the equipment itself does, through signals like vibration, temperature, ultrasonic noise, oil particulates, or motor current.

How predictive maintenance works

It runs in three layers. First, sensors (or manual readings) capture a condition signal over time. Second, a baseline of normal behavior is established. Third, when readings drift outside normal — a bearing's vibration climbing, a motor drawing more current — the system flags a developing fault and generates a work order with lead time to plan parts and labor. Modern CMMS platforms increasingly fold in AI models that learn each asset's failure signature from its own history.

Predictive vs preventive maintenance

Preventive maintenance acts on a fixed schedule whether the asset needs it or not, which means some work is done too early (wasting component life) and some failures still slip through between intervals. Predictive maintenance acts only on evidence, so it cuts both unnecessary work and surprise breakdowns. The trade-off is setup: PdM needs sensors or readings and a baseline, where preventive needs only a calendar.

Where to start with predictive maintenance

Begin with your most critical, most expensive-to-fail assets — the ones whose downtime hurts most. Pick one measurable signal (vibration on rotating equipment is the classic starting point), capture it regularly, and watch for trend changes. You do not need a full sensor rollout to start; even routine manual readings logged in a CMMS turn into a predictive trend over time.

Do I need expensive sensors for predictive maintenance?

Not to start. Manual condition readings (temperature, vibration pens, oil samples) logged consistently in a CMMS build a usable trend. Permanent sensors pay off on the most critical assets.

Is predictive maintenance the same as condition-based maintenance?

They are closely related. Condition-based maintenance acts when a reading crosses a threshold; predictive maintenance goes further and forecasts the failure ahead of time, often with models.