A review paper on An Analysis of AI-Assisted Automatic PCB Defect Identification

Abstract

Modern electronics depend on printed circuit boards (PCBs) and it is crucial to ensure their quality during manufacture by detecting defects. The precision, adaptability, and flexibility of conventional automated inspection techniques, such as Automated Optical Inspection (AOI) are constrained.

Automating PCB flaw identification has showed potential thanks to recent developments in artificial intelligence (AI), specifically machine learning (ML) and deep learning (DL). This study examines AI-based methods for PCB flaw identification, assesses their effectiveness, talks about the main obstacles, and suggests future areas of inquiry for the area. Manufacturers may create PCB inspection systems that are quicker, more precise and more flexible by incorporating AI.