Title: Artificial Intelligence: Theory, Tools and Real-World Applications
Editors: Prof. Dr. A. Shameem and Dr. J. Rengamani
ISBN: 978-81-69857-67-3
Chapter: 8
DOI: https://doi.org/10.59646/819/20
Author: Ms. Sherine Dominick
Abstract
Computer Vision (CV) has emerged as a transformative technology in industrial quality inspection, enabling automated, accurate, and real-time detection of defects in manufacturing processes. Traditional inspection methods often rely on human operators, which can be time-consuming, inconsistent, and prone to errors due to fatigue and subjective judgment. The practical implementation of computer vision systems addresses these challenges by utilizing cameras, image processing algorithms, and artificial intelligence techniques to analyze products and identify defects with high precision. Industries such as automotive, electronics, pharmaceuticals, food processing, and textile manufacturing increasingly adopt computer vision solutions to ensure product quality, reduce operational costs, and improve production efficiency. Modern computer vision systems employ machine learning and deep learning models to detect surface defects, dimensional inaccuracies, assembly errors, and packaging inconsistencies. High-resolution imaging devices capture product images, which are then processed through advanced algorithms for feature extraction, pattern recognition, and classification. Real-time inspection capabilities enable immediate identification and removal of defective products from production lines, minimizing waste and enhancing customer satisfaction. Furthermore, the integration of Industrial Internet of Things (IIoT) technologies allows seamless data collection, monitoring, and predictive maintenance. Despite significant advantages, challenges such as varying lighting conditions, complex product geometries, data annotation requirements, and implementation costs remain important considerations. However, continuous advancements in artificial intelligence, edge computing, and high-speed imaging technologies are making computer vision systems more accessible and efficient. The practical deployment of computer vision for industrial quality inspection represents a crucial step toward smart manufacturing and Industry 4.0, providing organizations with improved quality control, enhanced productivity, and sustainable competitive advantages.
Keywords: Computer Vision; Industrial Quality Inspection; Artificial Intelligence; Machine Learning; Deep Learning; Defect Detection; Image Processing; Smart Manufacturing; Industry 4.0; Automated Inspection; Quality Control; Industrial Automation.