Development of an Automated PCB Inspection, Error Statistics, and Classification System

Abstract

In the electronics manufacturing industry, Printed Circuit Boards are critical to electronic devices, and their quality directly affects product performance and reliability. Common assembly defects, such as missing components, misalignment, or wrong parts, must be detected promptly to reduce waste and maintain reputation. In Vietnam, PCB inspection is largely manual, limiting speed, accuracy, and consistency. The system integrates a YOLOv5-based machine vision module for detecting missing and misaligned components, a Siemens S7-1200 PLC for controlling an XY gantry and conveyor system, and a web interface for real-time monitoring. The primary contributions include: a fully integrated cyber-physical prototype suitable for educational and small-scale industrial use; a novel method for component misalignment detection using fiducial-based relative positioning; and seamless communication between vision, control, and HMI modules. Experimental results on two common PCB types, L298N and ULN2003, demonstrate a classification and error detection accuracy of up to 93%. The system achieves a throughput suitable for laboratory and small-batch production, with a positioning accuracy of ±0.5 mm. The system aims to achieve high accuracy, fast processing, and practical applicability in production lines.