Computer Vision in Manufacturing
We recently completed a computer vision project for a manufacturing client that reduced quality control costs by 60%. Here's what we learned.
The Challenge
Our client, a precision parts manufacturer, was using manual inspection for quality control. This was:
- Slow (30 seconds per part)
- Inconsistent (human fatigue)
- Expensive (multiple inspectors needed)
Our Solution
We built a real-time defect detection system using:
- Cameras: Industrial cameras with controlled lighting
- Model: Custom CNN trained on defect images
- Inference: Edge deployment on NVIDIA Jetson
- Integration: Direct PLC connectivity for rejection
Results
After 6 months in production:
- 99.7% defect detection accuracy
- 3-second inspection time
- ROI achieved in 8 months
- Zero customer complaints about quality
Lessons for Manufacturing AI
1. Lighting is everything - Consistent lighting beats better models 2. Edge deployment matters - Millisecond latency requirements 3. Involve operators early - They know the defects best 4. Plan for maintenance - Cameras need cleaning, models need retraining
