Find the 10 variables
that drive your scrap.
Jemba ranks hundreds of process parameters by their real impact on defects, isolates the few that matter, and hands you an apply-ready operating range — with the € gain quantified before you touch the line.
The root cause is in your data.
It’s just buried in 700+ variables.
Six Sigma studies take weeks and test a handful of factors at a time. Meanwhile scrap keeps shipping. The real driver is usually an interaction between a few parameters no one thought to pair — the kind of pattern a model finds in minutes and a spreadsheet never will.
718 in.
10 that matter out.
Jemba scores every parameter by its contribution to scrap, exposes the interactions, and gives you an optimal window per driver — pushed straight to the line over OPC-UA.
- Variable importance by SHAP, not by hunch.
- An optimal range per parameter (e.g. crimp force 4.2–4.5 kN).
- A quantified gain before you act: scrap, yield, € / month.
Trusted on the floor by 450+ factories.
Jemba is built by TeepTrak — the production-monitoring platform manufacturers already run on the line, proven across 30+ countries.
From defect to fix,
in four steps.
Connect
Bring in process + quality data via TeepTrak, CSV or API.
Correlate
Jemba ranks the drivers and finds the interactions.
Recommend
Get an optimal window per parameter, with € gain.
Apply
Push setpoints over OPC-UA or a work order.
One platform.
Four ways to win on the line.
Stop shipping scrap you could have explained.
Book a 15-minute demo or start a free trial. 48-hour setup, no data scientist required.
Frequently asked questions
How does Jemba find the cause of quality defects?
It correlates hundreds of process variables against your quality outcomes to rank the factors most linked to scrap and defects.
Can it handle hundreds of parameters?
Yes. Jemba processes 700+ variables to find the combinations that drive quality — something that is impractical to do by hand.
Do I need to label data?
No heavy labeling. Jemba works from your existing process and quality records.
What kind of result can we expect?
Teams typically pinpoint the few parameters driving most scrap, then adjust them to raise first-pass yield.
