Vision QA System
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Vision QA System

Solution type: Manufacturing & Production

The Challenge

Manufacturers running visual quality inspection with human inspectors face well-documented limitations: eye fatigue after 90–120 minutes causes missed defects, throughput is capped by human speed, coverage is sample-based not 100%, and defects that escape to customers trigger costly recalls and warranty claims.

Our Solution

We deploy real-time computer vision systems across production lines — cameras at every quality gate, with custom-trained object detection models identifying defect types at production line speeds. 100% coverage, zero fatigue, automated rejection of non-conforming parts.

What We Built

  • Design and install industrial camera arrays at critical inspection points along production lines
  • Collect and label training images covering all defect types across varying lighting and orientation conditions
  • Train and optimise YOLOv9 / custom vision models for edge deployment on NVIDIA Jetson devices at each station
  • Build real-time alerting and automated rejection — defective parts trigger air ejectors automatically
  • Create quality dashboards with live defect rates by line, shift, and defect type — integrating with ERP systems

Results: Before vs After

MetricBeforeAfterChange
Defect escape rate1.5–2% (human inspection)< 0.1%↓ 90–95%
Inspection cost/shiftHigh (dedicated inspectors)Near zero (automated)↓ 90%+
Throughput speedHuman-limitedFull line speed↑ 40–60%
CoverageSample-based (~5%)100% of output↑ 20× coverage
Payback periodTypically 3–6 monthsOne recall avoided pays for it

Timeline

Typically 10 weeks including hardware installation

Technologies

YOLOv9PyTorchNVIDIA Jetson OrinOpenCVFastAPIInfluxDBGrafana

Automated vision inspection eliminates the #1 source of quality escapes — human fatigue — and turns every camera on your line into a tireless, sub-millisecond quality decision-maker.

What this means for your production line

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