Machine Learning for Sustainable Manufacturing in Industry 4.0: Concept, Concerns and Applications

Machine Learning for Sustainable Manufacturing in Industry 4.0: Concept, Concerns and Applications

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The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods.Focusses on machine learning applications in Industry 4.0 ecosystem, such as resource optimization, data analysis, and predictions.Highlights the importance of the explainable machine learning model in the manufacturing processes.Presents the integration of machine learning and big data analytics from an industry 4.0 perspective.Discusses advanced computational techniques for sustainable manufacturing.Examines environmental impacts of operations and supply chain from an industry 4.0 perspective.This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.
LF/28143566/R

Data sheet

Name of the Author
(eds.)
Raman Kumar
Sehijpal Singh Khangura
Sita Rani
Language
English
Series
Mathematical Engineering, Manufacturing, and Management Sciences
ISBN
9781003453567
Release date
2023

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Machine Learning for Sustainable Manufacturing in Industry 4.0: Concept, Concerns and Applications

The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using mac...

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