Shulph Ink
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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- More about 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 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.
Format: Hardback
Length: 234 pages
Publication date: 03 November 2023
Publisher: Taylor & Francis Ltd
The book delves into the latest advancements in error reduction, resource optimization, and revenue growth in sustainable manufacturing through the integration of machine learning. It presents the integration of smart technologies, including machine learning, in the field of Industry 4.0, aiming to enhance product quality and optimize manufacturing methods.
Focusing on machine learning applications within the Industry 4.0 ecosystem, the book highlights resource optimization, data analysis, and predictions. It emphasizes the importance of explainable machine learning models in manufacturing processes. The integration of machine learning and big data analytics from an Industry 4.0 perspective is explored, as well as advanced computational techniques for sustainable manufacturing.
The book also examines the environmental impacts of operations and supply chain from an Industry 4.0 perspective, providing valuable insights into sustainable manufacturing practices.
This comprehensive book offers scientific and technological insights into sustainable manufacturing by covering a wide range of machine learning applications, including fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in Industry 4.0, as well as explainable machine learning models for Industry 4.0. Serving as an ideal reference text for senior undergraduate, graduate students, and academic researchers in fields such as mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering, the book contributes to the understanding and development of sustainable manufacturing technologies.
Weight: 620g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032393056
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