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Artificial Intelligence and Machine Learning in the Thermal Spray Industry : Practices, Implementation, and Challenges

By: (Author) Gaurav Prashar , (Author) Hitesh Vasudev , (Author) Jashanpreet Singh , (Author) Lalit Thakur

Manufacture on Demand

Ksh 20,700.00

Format: Hardback or Cased Book

ISBN-10: 103250224X

ISBN-13: 9781032502243

Series: Multi-Scale and Multi-Functional Materials

Publisher: Taylor & Francis Ltd

Imprint: CRC Press

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Dec 1st, 2023

Print length: 128 Pages

Weight: 349 grams

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Artificial Intelligence and Machine Learning in the Thermal Spray Industry highlights how Artificial Intelligence and Machine Learning techniques are used in the Thermal Spray industry. It sheds light on AI’s versatility and applicability in solving problems related to conventional simulation and numeric modeling techniques.

This book details the emerging area of the induction of expert systems in thermal spray technology, replacing traditional parametric optimization methods like numerical modeling and simulation. It promotes, enlightens, and hastens the digital transformation of the surface engineering industry by discussing the contribution of expert systems like Machine Learning (ML) and Artificial Intelligence (AI) toward achieving durable Thermal Spray (TS) coatings.

Artificial Intelligence and Machine Learning in the Thermal Spray Industry: Practices, Implementation, and Challenges

highlights how AI and ML techniques are used in the TS industry.

It sheds light on AI’s versatility, revealing its applicability in solving problems related to conventional simulation and numeric modeling techniques. This book combines automated technologies with expert machines to show several advantages, including decreased error and greater accuracy in judgment, and prediction, enhanced efficiency, reduced time consumption, and lower costs. Specific barriers preventing AI’s successful implementation in the TS industry are also discussed. This book also looks at how training and validating more models with microstructural features of deposited coating will be the center point to grooming this technology in the future. Lastly, this book thoroughly analyzes the digital technologies available for modeling and achieving high-performance coatings, including giving AI-related models like Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) more attention.

This reference book is directed toward professors, students, practitioners, and researchers of higher education institutions working in the fields that deal with the application of AI and ML technology.


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