Computer Vision Pipeline for Manufacturing QC
Built an end-to-end computer vision system for automated quality control in manufacturing. Reduced inspection time by 80% while maintaining 99.5% accuracy in defect detection.
Technologies Used
Project Overview
Developed a comprehensive computer vision pipeline for automated quality control in manufacturing environments. The system processes high-resolution images from production lines in real-time, detecting various types of defects with exceptional accuracy.
System Architecture: ā¢ Multi-stage CNN for defect classification ā¢ Real-time image preprocessing pipeline ā¢ Edge deployment with NVIDIA Jetson ā¢ Integration with existing MES systems ā¢ Automated reporting and alerting
The solution handles multiple defect types including scratches, dents, color variations, and dimensional inconsistencies. The system was deployed across 5 manufacturing facilities and processes over 10,000 parts daily.
Key Challenges
- Handling varying lighting conditions across facilities
- Training with limited defect samples
- Real-time processing requirements (<100ms)
Impact & Results
Deployed across 5 manufacturing facilities, processing 10,000+ parts daily. Reduced quality control costs by $2M annually while improving product quality.