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Keywords

Artificial Intelligence in Manufacturing, Machine Learning for Smart Manufacturing, Industry 4.0 Technologies, Industry 5.0 Applications, Smart Factory Systems, Industrial Internet of Things, AI-Driven Manufacturing, Predictive Maintenance Systems, Deep Learning in Manufacturing, Computer Vision for Quality Inspection, Digital Twins in Manufacturing, Cyber-Physical Systems, Manufacturing Data Analytics, Sustainable Manufacturing Technologies, Industrial Automation Systems, Human-AI Collaboration, Intelligent Manufacturing Systems, Industrial Cybersecurity, Data-Driven Manufacturing, Natural Language Processing in Industry

Artifical Intelligence and Machine Learning for Smart Manufacturing

Language: English | Imprint: NIPA

Hardback

ISBN: 9789372194371
Pages: 360 | Length: 152 mm | Breadth: 20 mm | Height: 229 mm | Weight: 850 GSM
Print Book Price: 200.00 USD (Get 10% OFF)
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EBook

EISBN: 9789372193978
Ebook Individual Price: 0.00 USD
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eChapter

eChapter details: Available in the Content section below.
<p style="text-align:justify">The book provides a comprehensive introduction to the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in modern industrial systems. The book explores how smart manufacturing technologies are reshaping conventional production environments into intelligent, connected, and data-driven ecosystems. It systematically covers core concepts of Industry 4.0, data acquisition, analytics, statistical modeling, predictive maintenance, computer vision, deep learning, digital twins, and Industrial Internet of Things (IIoT) applications. Emphasis is also placed on human&ndash;AI collaboration, sustainable manufacturing practices, Industry 5.0 principles, cybersecurity, ethical considerations, and global industrial standards.</p> <p style="text-align:justify">Combining theoretical foundations with practical industrial applications, the book serves as a valuable resource for researchers, academicians, graduate students, and industry professionals in manufacturing engineering, industrial automation, artificial intelligence, and data science. It aims to support the development of intelligent, resilient, and sustainable manufacturing systems for the future.</p>
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