Application of machine vision for quality control in production
TL;DR
Recommendations are formulated for choosing an optimal machine vision architecture for different types of production, and promising directions for further development of the technology in the context of industrial digital transformation are identified.
Abstract
This article examines the application of machine vision systems for automated quality control at manufacturing enterprises. It analyzes the current state of the market, the hardware structure of visual inspection systems, and the technological capabilities of 2D, 3D, hyperspectral, and intelligent machine vision for defect detection, dimensional measurement, assembly verification, marking inspection, and packaging control. A classification of production tasks based on the feasibility of machine vision implementation is proposed. Special attention is paid to the selection of cameras, lenses, lighting, image processing algorithms, and integration with programmable logic controllers, MES, and ERP systems. The article presents accuracy indicators, methods for evaluating algorithm performance, and recommendations for reducing false rejects and missed defects. Based on the analysis of practical experience from Russian and international enterprises, recommendations are formulated for choosing an optimal machine vision architecture for different types of production, and promising directions for further development of the technology in the context of industrial digital transformation are identified.