Inspection Result Classification uses AI to grade inspection results consistently, enabling fewer escapes and less false scrap, by classifying images and measurements against quality criteria, across quality inspection and test.
Quality inspection produces images and measurements that inspectors grade against criteria by eye. Throughput pressure and fatigue make grading inconsistent, so defects escape and good parts are scrapped, both at cost.
The AI performs classification on inspection images, measurements, and quality criteria, assigning each part a result category so borderline cases are routed to a human and clear cases pass automatically.
Improves inspection classification accuracy and reduces both escaped defects and false scrap.
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