Overview
Machine data is continuously analyzed for the early warning signs of failure, so maintenance can be scheduled before a breakdown causes downtime, not after.
What's included
1
Failure pattern detection
Identify early warning signs from live and historical sensor data.
2
Maintenance scheduling recommendations
Get suggested service windows before a failure occurs.
3
Downtime & cost forecasting
Estimate the cost and impact of a potential failure ahead of time.
4
Asset health scoring
Track a running health score for every piece of equipment.
How it works
Baseline
Analyze historical performance data to establish normal operating patterns.
Model
Train failure-detection models on your specific equipment and conditions.
Launch
Go live with maintenance recommendations tied to real asset health scores.