Automated Vision Inspection
Quality Control Automation
4 months
OpenCVPythonCamera IntegrationMachine LearningC++Industrial Cameras
99.5%
Defect Detection Rate
0.8s
Inspection Time/Board
300%
Throughput Increase
2 mo
Payback Period
Overview
Designed and implemented an automated vision inspection system for PCB assembly verification. The system inspects populated circuit boards for component presence, orientation, and solder quality at production line speed, replacing manual visual inspection that was both slow and error-prone. The project included camera selection, lighting design, algorithm development, and integration with the existing manufacturing execution system.
Challenges
- 1Manual inspection missing 3-5% of defects
- 2Inspection bottleneck limiting line throughput
- 3Variable lighting conditions affecting image quality
- 4Need to detect multiple defect types with single system
Solutions
- Designed custom lighting enclosure for consistent illumination
- Developed multi-stage inspection algorithm: presence → orientation → solder
- Implemented ML-based defect classification for edge cases
- Created operator interface with defect visualization and statistics