In today's competitive manufacturing environment, maintaining product quality ensures operational efficiency, customer satisfaction, and regulatory compliance. Traditional quality control methods can be time-consuming, containing human error. Artificial intelligence (AI) transforms industrial quality control by enabling real-time monitoring, automated detection, predictive analytics, and data-driven decision-making. Through advanced technologies, AI applications help manufacturers identify quality issues, reduce production waste, and optimize process performance. As industries embrace digital transformation, AI-driven quality control systems achieve higher standards of reliability, productivity, and competitiveness. Strengthening Industrial Quality Control With AI Applications explores how AI improves accuracy, efficiency, and consistency in industrial sectors. It examines the benefits, challenges, and real-world applications of AI in detection, process monitoring, quality assurance, and decision-making in manufacturing environments. This book covers topics such as manufacturing, quality control, and data science, and is a useful resource for engineers, business owners, academicians, researchers, and scientists.
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Rahul K. Patel is a seasoned cybersecurity and information systems management professional with extensive scholarly contributions highlight his thought leadership in AI, digital infrastructure, and secure system design. Dr. Patel’s research spans AI-driven digital literacy where he presents a framework for higher education and workforce collaboration in response to the AI revolution as well as studies on AI-based recommendation systems, such as an analysis of the accuracy of OTC medication suggestions generated by commercial AI platforms. He is the author of AI Frameworks and Tools for Software Development (2025), which provides a comprehensive exploration of how artificial intelligence can be strategically integrated into the software development lifecycle. His work also tackles security and privacy within emerging technologies: from leveraging clustering algorithms for predictive analytics in blockchain networks to exploring privacy-preserving architectures and cloud security fortified by distributed ledger technologies. With a PhD in Management of Information Systems, Dr. Patel serves as an Adjunct Industry Associate Professor at the Illinois Institute of Technology.
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Paperback. Condition: new. Paperback. In today's competitive manufacturing environment, maintaining product quality ensures operational efficiency, customer satisfaction, and regulatory compliance. Traditional quality control methods can be time-consuming, containing human error. Artificial intelligence (AI) transforms industrial quality control by enabling real-time monitoring, automated detection, predictive analytics, and data-driven decision-making. Through advanced technologies, AI applications help manufacturers identify quality issues, reduce production waste, and optimize process performance. As industries embrace digital transformation, AI-driven quality control systems achieve higher standards of reliability, productivity, and competitiveness. Strengthening Industrial Quality Control With AI Applications explores how AI improves accuracy, efficiency, and consistency in industrial sectors. It examines the benefits, challenges, and real-world applications of AI in detection, process monitoring, quality assurance, and decision-making in manufacturing environments. This book covers topics such as manufacturing, quality control, and data science, and is a useful resource for engineers, business owners, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798337397269
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Paperback. Condition: new. Paperback. In today's competitive manufacturing environment, maintaining product quality ensures operational efficiency, customer satisfaction, and regulatory compliance. Traditional quality control methods can be time-consuming, containing human error. Artificial intelligence (AI) transforms industrial quality control by enabling real-time monitoring, automated detection, predictive analytics, and data-driven decision-making. Through advanced technologies, AI applications help manufacturers identify quality issues, reduce production waste, and optimize process performance. As industries embrace digital transformation, AI-driven quality control systems achieve higher standards of reliability, productivity, and competitiveness. Strengthening Industrial Quality Control With AI Applications explores how AI improves accuracy, efficiency, and consistency in industrial sectors. It examines the benefits, challenges, and real-world applications of AI in detection, process monitoring, quality assurance, and decision-making in manufacturing environments. This book covers topics such as manufacturing, quality control, and data science, and is a useful resource for engineers, business owners, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798337397269
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Paperback. Condition: new. Paperback. In today's competitive manufacturing environment, maintaining product quality ensures operational efficiency, customer satisfaction, and regulatory compliance. Traditional quality control methods can be time-consuming, containing human error. Artificial intelligence (AI) transforms industrial quality control by enabling real-time monitoring, automated detection, predictive analytics, and data-driven decision-making. Through advanced technologies, AI applications help manufacturers identify quality issues, reduce production waste, and optimize process performance. As industries embrace digital transformation, AI-driven quality control systems achieve higher standards of reliability, productivity, and competitiveness. Strengthening Industrial Quality Control With AI Applications explores how AI improves accuracy, efficiency, and consistency in industrial sectors. It examines the benefits, challenges, and real-world applications of AI in detection, process monitoring, quality assurance, and decision-making in manufacturing environments. This book covers topics such as manufacturing, quality control, and data science, and is a useful resource for engineers, business owners, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798337397269
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Taschenbuch. Condition: Neu. Strengthening Industrial Quality Control With AI Applications | Rahul K. Patel | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337397269 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 136369140
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In today's competitive manufacturing environment, maintaining product quality ensures operational efficiency, customer satisfaction, and regulatory compliance. Traditional quality control methods can be time-consuming, containing human error. Artificial intelligence (AI) transforms industrial quality control by enabling real-time monitoring, automated detection, predictive analytics, and data-driven decision-making. Through advanced technologies, AI applications help manufacturers identify quality issues, reduce production waste, and optimize process performance. As industries embrace digital transformation, AI-driven quality control systems achieve higher standards of reliability, productivity, and competitiveness. Strengthening Industrial Quality Control With AI Applications explores how AI improves accuracy, efficiency, and consistency in industrial sectors. It examines the benefits, challenges, and real-world applications of AI in detection, process monitoring, quality assurance, and decision-making in manufacturing environments. This book covers topics such as manufacturing, quality control, and data science, and is a useful resource for engineers, business owners, academicians, researchers, and scientists. Seller Inventory # 9798337397269