Case Study · Computer Vision
Catching defectsat line speed
We put computer vision on the production line to inspect every unit in real time — flagging defects a human eye would miss at speed, cutting scrap in half and freeing inspectors for the judgment calls that matter.
The challenge
Manual inspection couldn’t scale
Inspectors could only spot-check a fraction of output, so defects slipped through to customers while good units were sometimes scrapped on a bad call. As line speed rose, the gap only widened.
We trained defect-detection models on labeled imagery and deployed them on edge hardware beside the line — inspecting every unit in real time, flagging anomalies instantly and feeding a dashboard that surfaces trends before they become recalls.
- Every unit inspected, not a sample
- Defects caught before they ship
- Less good product scrapped
- Trends flagged before recalls
What we built
The solution
Defect Detection
Defect DetectionVision models trained to flag surface and dimensional defects in real time.
Edge Deployment
Edge DeploymentRuns on hardware beside the line for sub-50ms, offline-capable inference.
Quality Dashboard
Quality DashboardLive defect trends and root-cause views for line managers and quality.
“Latency dropped, accuracy climbed and our scrap halved. The inspection system basically runs itself now.”
Marcus Chen · Director of Engineering