It sees the failure coming and orders the part first.
The AI watches every asset's sensor trend, predicts the breakdown before it stops the line, raises the work order, and procures the spare at the best-quoted price, all before a tech lifts a wrench. Press run.
Assets watched
146
At risk
·
Unplanned downtime
8.4%
Parts cost
·
Asset health
sensor trend
PRESS-02 bearing
vibration nominal
CNC-01 spindle
temp rising · 88% to limit
WELD-03 wire feed
within range
CONV-07 motor
current draw normal
Auto-response · CNC-01
predicted 6 days out
1
Predict
Spindle bearing wear, fail in ~6 days
2
Work order
Scheduled in next planned window
3
Source part
3 vendors quoted, best price picked
4
PO raised
Spare ordered, arrives before window
Predictive, not reactive. The part is on the dock before the line stops.
The impact
The failure is caught and the spare is ordered before the line stops.
Sensor trends predict the breakdown, the work order is scheduled and the part is sourced at the best quote, cutting unplanned downtime and rush-shipping cost.
Typical projectionManufacturing · industry benchmark
Unplanned downtime
8.4%→1.9%
▲ line keeps running
Spare parts spend
Baseline→-22%
▲ best-quoted, no rush fees
Breakdowns caught early
Reactive→6 days
▲ predicted ahead
Unplanned downtime by week
▲ -6.5 ptsLast 6 weeks
With TRIVOX
Projection, not a guaranteed result. Typical estimated range for businesses in this sector based on typical volume. Individual results vary. Shown as system capability, not a specific client case.
