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Manufacturing
Vortex Components
Defect rate 4.1% → 0.6% with vision + telemetry
4.1%→0.6%
Defect rate
4.1%→0.6%
+34%
Throughput
baseline→+34%
11 wks
Time to ROI
n/a→11 weeks
The challenge
What wasn't working
After a decade of process work, defect rate plateaued at 4.1%. Every defective unit shipped was a customer escalation, a return, and an internal RCA. The QC team was reactive — discovering issues days after they originated.
The architecture
How we solved it
A vision + telemetry pipeline at the line level: cameras flag visual anomalies in real time, sensors detect subtle drift in machine output, both feed an anomaly model that routes alerts to a quality engineer the moment a part exits the line. No part ships without passing this gate.
Stack used
Custom vision modelAWS IoTGrafanaPagerDutyOPC-UA bridge
The result
What happened
Defect rate dropped to 0.6% within 8 weeks of deployment. Throughput rose 34% because the line stops less often for downstream rework. Customer escalations dropped 81% in the same window.
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We've tried three automation consultancies. Aiprosol is the only one that delivered a roadmap with real numbers attached and then actually hit them.
Daniel ChenCOO · Vortex Components
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