APPLICATION OF COMPUTER VISION IN AUTOMATED QUALITY CONTROL SYSTEMS
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The article analyzes application of computer vision in automated quality control systems. Computer vision technologies improve automated inspection by identifying surface defects, dimensional errors, and production inconsistencies. Integration with machine learning increases accuracy and reduces human error. The aim of the study was to evaluate the technical, functional, and practical significance of this approach in modern engineering systems. The study used analytical review, comparative assessment, and synthesis of current engineering literature. The results show that the investigated technology improves operational efficiency, reliability, safety, and sustainability. The findings may be useful for engineers, researchers, and managers involved in the modernization of industrial and technological processes.
