AI approach towards Quality Control Systems for Zero Defect Manufacturing

Artificial intelligence (AI) has been included into quality control systems as a result of the drive for zero defect manufacturing, which has completely changed industrial processes.The application of AI-driven quality control systems in manufacturing settings is examined in this paper, with a focus on the systems' real-time fault detection, prediction, and preventive capabilities.A complete quality assurance framework is produced by combining cutting-edge sensor, computer vision, and machine learning methods.The study looks at how well these techniques are effective in cutting down on waste, lower error rates, and enhance overall product quality.Case studies from a range of industries show significant improvements in efficiency in production and defect detection accuracy.The report also discusses workforce adaptation, data management, and system integration issues.The findings indicate how AI powered quality control systems have the potential to transform manufacturing procedures, also highlights future work in autonomous AI systems, integration with Industry 4.0 paradigms, and sustainable manufacturing practices opening the door to zero defect production and boosting competitiveness in the global market.Also the process real time data generated and can be used for industry as well the customer.