Vision-based inspection catches defects at line speed with consistency humans can't sustain — the wins come from problem selection, lighting
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High-volume, visually-expressed defects with labeled examples available — surface flaws, assembly verification, label/print checks; subtle judgment calls stay human-assisted, routed by confidence.
Lighting, optics, and mounting determine ceiling accuracy — the boring imaging engineering outperforms model heroics on bad images every time.
Edge inference at line speed, borderline cases queued for human review, and those reviews feeding retraining — accuracy as a managed metric, with drift monitoring as products and materials change.
Defect events into MES/quality systems, stop/divert signaling, and dashboards tying catch-rates to scrap and rework dollars — the ROI report writes the expansion roadmap.
Skipping the discipline this article describes until an incident, audit, or stalled project forces it — every practice above is cheaper adopted early than retrofitted under pressure.
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