Abstract
The evolution of automated quality control (AQC) in manufacturing reflects the convergence of digital innovation and industrial precision. From rudimentary visual inspection methods to today's advanced AI-integrated systems, AQC has revolutionized how defects are detected, analyzed, and prevented. This paper traces the historical development of AQC technologies, outlines modern applications using computer vision and machine learning, and highlights the integration of Industry 4.0 tools to enhance real-time inspection and data-driven process control. The study also explores future trends, challenges, and the impact of automation on productivity and labor dynamics.
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