Automated Quality Inspection Machine Using Computer Vision

Abstract

Quality assurance is critical in manufacturing, yet human error in visually assessing product quality persists due to the tedious nature of the task. While solutions like lean manufacturing have been proposed, Computer Vision offers a promising alternative. This branch of artificial intelligence automates visual perception tasks using techniques such as image processing and neural network training. Currently limited to basic applications due to computational constraints, the future of Computer Vision holds promise for expanding into material property detection, product design analysis, and automation of critical manufacturing processes. Despite its limitations, ongoing research, including advancements in Reinforcement Learning, suggests the potential for comprehensive problem-solving capabilities in the field. With continued development, Computer Vision stands to revolutionize quality assessment and streamline manufacturing processes.