AI & Analytics
Automated Work Orders
Physics and ML models detect issues, assess severity, create work orders, assign technicians, and pre-order parts -- automatically. Close the loop from detection to resolution.
Automation Workflow
Trigger Sources
Five different model types can trigger automated work orders.
| Source | Example Trigger | WO Type |
|---|---|---|
| Physics Model | Pump wire-to-water efficiency drops below 65% | Corrective |
| Anomaly Detection | Multi-algorithm consensus flags bearing vibration pattern | Inspection |
| RUL Prediction | Seal remaining useful life falls below 21 days | Preventive |
| Threshold Alarm | Motor winding temperature exceeds 85C for >10 minutes | Emergency |
| Drift Detection | Sensor calibration drift detected (flow meter reads 8% low) | Calibration |
Configuration Options
Configurable Thresholds
Set trigger conditions per equipment type: efficiency drop >10%, vibration >4.5 mm/s, RUL <30 days. Combine multiple conditions with AND/OR logic.
Routing Rules
Route by equipment type, location, severity, or time of day. Night shift critical alerts go to on-call lead; daytime P3s go to area technician.
Parts Pre-Ordering
Link failure modes to bill-of-materials. When a bearing failure is predicted, the system checks warehouse stock and creates a PO if needed.
Escalation Chains
If a P1 work order is unacknowledged after 30 minutes, escalate to shift supervisor. After 60 minutes, escalate to maintenance manager.
ML Confidence Gating
Only create work orders when model confidence exceeds your threshold. 90% confidence = auto-create. 70-90% = suggest. Below 70% = log only.
De-Duplication
Suppress duplicate work orders for the same asset and failure mode within a configurable cooldown window. Merge related alerts into a single WO.
Close the Loop Automatically
From anomaly detection to work order completion -- no manual intervention required. Your team focuses on fixing, not dispatching.