History
Analytics & Anomaly Trends
Six months of fleet-wide anomaly density, fault-type distributions, and model accuracy — all scoped to the filters you care about.
Anomaly Density
Daily anomaly intensity across the fleet
2,184 events·+12% vs prev period
Model Accuracy · 90 days
Precision / Recall against labeled outcomes
Precision
0.942
+1.3%
Recall
0.911
+0.7%
F1
0.926
+1.0%
Fault Distribution
Share of predicted faults by type
Bearing wear42%
Misalignment24%
Lubrication16%
Thermal12%
Electrical6%
MTBF
1,284h
MTTR
2h 18m
Prevented
18 incidents
Saved
$412k est.
CNC Mill A1
Health index · 7d trend
94Score
Press B4
Health index · 7d trend
71Score
Robot R7
Health index · 7d trend
42Score
Pump T9
Health index · 7d trend
76Score