Scrap Count / Total CountQuality Intelligence · Product
Quality Intelligence
Protect yield and catch defects early — manual inspection, scrap reasons, and Vision Intelligence review with Human-in-the-loop.
- Operator inspection forms on the live timeline
- Scrap / rework codes feeding OEE Quality
- Vision Intelligence: defect events → HITL → disposition (model Plug-in ready)
Illustrative sceneOutcomes
What you'll gain
- Fewer silent scrap escapes
- Traceable holds and releases
- Pareto of defect reasons by shift
- Quality AI recommendations with approval
Trusted math
Formulas (locked)
Rework Count / Total CountGood Count / Total CountProduct tour
Inside Quality Intelligence
Inspection overlays, scrap Pareto, and Vision Review queue on the same Industrial Core as Production Intelligence.
Illustrative product scenario — not a customer deployment or live plant feed.
Shift timeline
Deterministic sample values show the interaction pattern. Production deployments bind this view to governed Industrial Core signals.
| Quality Intelligence · Product signal | 97% |
|---|---|
| Context | Deterministic sample values show the interaction pattern. Production deployments bind this view to governed Industrial Core signals. |
Numeric ranges, yes/no, and checklist items — tablet-sized controls.
Camera events with confidence scores. Never silent scrap — ApproveHitl required.
Day on the floor
How it changes your day
- Operators run checks when production events fire
- Scrap reasons replace end-of-shift guesswork
- Vision suggestions wait for human disposition
- Quality factor stays consistent with oee-engine
Accuracy
Quality you can audit
Formulas from knowledge/quality-analytics.md. Vision model_id is optional — Plug-in later without redesign.
- RBAC on hold / release / scrap
- Audit on every vision disposition
- Genealogy retains scrap reason codes
Review your factory improvement case
Bring one production line, its current data sources, and a priority loss. We will map the measurement, workflow, and proof of value.