Automated Printed Circuit Board Inspection System using NI Vision Builder and NI MyRio
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Abstract
To improve flaw identification in contemporary electronics manufacturing, this study introduces an automated printed circuit board (PCB) inspection system that integrates NI Vision Builder with NI MyRIO. The device effectively detects flaws like missing parts, open circuits, and over-etched traces by utilizing a high-resolution camera and sophisticated methods including color plane extraction and pattern matching. Real-time visualization, classification, and automated data recording are made possible via a LabVIEW-based interface, which makes the inspection process easy to use. A 92% accuracy rate was attained during testing on both bare PCBs and PCB assemblies, indicating better performance than conventional techniques. Although multi-layer and subsurface defect detection still presents difficulties, the system provides a scalable and affordable solution with the possibility to incorporate machine learning and sophisticated imaging in the future for increased adaptability.
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