An automated Printed Circuit Board (PCB) defects detection system

Kamaruddin, Shafie and Shamsulamri, Saiffaqrullah and Sharwazi, Muhammad Haziq Fakhri and Suhaimi, Muhammad Harith Ikhmal and Mohamad, Muhamad Ariff Othmani and Sukindar, Nor Aiman and Ahmad Azhar, Ahmad Zahirani (2025) An automated Printed Circuit Board (PCB) defects detection system. In: ICAMME 2024, 13 - 14 August 2024, Kuala Lumpur, Malaysia.

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Abstract

The study aims to develop an automated system leveraging modern machine learning techniques to identify defects in printed circuit boards (PCBs). Defects such as shorts, spurious copper, and missing holes can significantly compro-mise electronic devices’ reliability and performance. Traditional manual inspec-tion methods are time-consuming and error prone. Thus, this work addresses these issues by using a custom PCB defect dataset annotated with Roboflow and training a YOLOv5 model on Google Colab. The system integrates an Arducam Camera Module IMX219 with a Raspberry Pi 4 to capture high-resolution PCB images, which are then inspected in real-time for defects. By combining advanced object detection algorithms with affordable hardware, this method offers a practical and cost-effective solution for PCB defect detection. Results demonstrated that the system is highly accurate and efficient in detecting PCB flaws, with performance metrics of 0.92, 0.89, and 0.90 for precision, recall, and F1 score, respectively. This significantly enhances quality control in PCB manufacturing.

Item Type:	Proceeding Paper (Invited Papers)
Uncontrolled Keywords:	Defects detection, Machine vision, Printed circuit board (PCB)
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ210.2 Mechanical devices and figures. Automata. Ingenious mechanism. Robots (General) T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Manufacturing and Materials Engineering
Depositing User:	Dr. Shafie Kamaruddin
Date Deposited:	29 May 2025 11:07
Last Modified:	29 May 2025 13:14
URI:	http://irep.iium.edu.my/id/eprint/121243

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