Use cases
Four ways to find money in your machine data.
Same data foundation, four applications. Start with the one where your losses are biggest.
Quality Loop
A process that learns from every part.
- Catch deviations before they become scrap
- Find where problems start, and fix them for good
- Feed every outcome back: a self-learning process
Reading outside the normal band · flagged 14:32
Product Economics
Know what every part really costs.
- Quotes built on actual cost
- See which products lose money
- Standard costs that match the floor
A-4410−8.2 %
B-2207+1.4 %
C-1180−3.6 %
D-9032+0.9 %
PlannedActualMargin vs. quote
OEE & Optimization
See exactly where production time goes.
- Find the losses averages hide
- Fair comparisons across shifts and sites
- See losses as they happen
72%▼ 1 pt vs yesterday
A 78P 92Q 100
Shift A, minute by minute
RunningChangeoverStoppedMicro-stop
Shift A · now375on pace for 529
Yesterday A498
Yesterday B541
Yesterday C463
Predictive Maintenance
Fix machines before they fail.
- Fewer unplanned stops
- Service planned before the alarm limit
- Remote diagnostics across the installed base
Pump health64 %
Vibration4.9 mm/s
Useful life9 days
Service booked before alarm limit · no unplanned stop
Next step
Start with one machine. See measurable value in weeks.
Then we scale on proof, not promises.
WHICH MACHINE DO WE START WITH?