Computer Vision QA Cut Scrap Costs by $1.8M for a Manufacturer
Edge-deployed vision models inspecting 1,200 parts per minute with 99.2% defect detection accuracy.
Client: AlloyCore Manufacturing
The Challenge
Manual visual inspection at AlloyCore's plant missed subtle surface defects, driving a 3.4% scrap rate and occasional customer chargebacks. Inspectors covered only 60% of produced units.
Our Solution
We built a computer vision QA system using YOLO-based detection models fine-tuned on 120,000 labeled part images, deployed on edge devices beside each production line. React Native tablets gave line supervisors live defect heatmaps, and flagged units were automatically routed to rework stations.
The Results
Defect detection accuracy hit 99.2% with 100% inspection coverage at 1,200 parts per minute. Scrap rate fell from 3.4% to 0.6%, saving an estimated $1.8M annually.
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