Predictive Work Orders

Predictive work orders flag assets that look like they are sliding toward a problem, based on asset history, PM cadence, and similar-asset failures across the platform.

What you will see

Open Predictive work for a ranked list showing the asset, predicted issue (such as bearing wear or belt fatigue), confidence (low, medium, high), window (likely within 30, 60, or 90 days), and a short why. Click any row for full evidence: prior work orders, similar-asset patterns, sensor readings, and recommended actions.

How predictions work

Two engines feed the list. Pattern matching compares each asset against failure curves across your fleet and similar fleets. Anomaly detection flags deviations from expected operating ranges for sensor-instrumented assets, learning normal per unit. Confidence reflects signal strength and sample size.

How to act

A prediction is a hypothesis, not a directive. For high-confidence entries, schedule a precautionary inspection in one click. Adjust PM cadence if predictions cluster around a failure mode your PMs miss. For low-confidence entries, snooze for 14 days to re-evaluate. Do not generate corrective work orders blindly.

Calibration

Predictions improve with more closed work orders, consistent failure-cause fields, populated install dates and criticality, and sensor data. After about six months, predictions reflect your fleet specifically. Review weekly, close out predictions as Inspected with the outcome, and read the evidence panel.