株式会社極東書店トップ > 商品一覧 > Machine Learning for Sustainable Manufacturing in Industry 4.0 : Concept, Concerns and Applications.
商品詳細
Machine Learning for Sustainable Manufacturing in Industry 4.0 : Concept, Concerns and Applications.
・ISBN 978-1-032-39305-6 2024 hard GB£ 145.99
¥46,249.- (税込) ※(※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
・ISBN 978-1-032-59211-4 2025 paper GB£ 55.99
¥17,737.- (税込) ※(※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 978-1-003-45356-7
| 著者・編者 | Kumar, Raman / Rani, Sita / Singh Khangura, Sehijpal (eds.), |
|---|---|
| シリーズ | Mathematical Engineering, Manufacturing, and Management Sciences |
| 出版社 | (CRC Pr., US) |
| ページ数 | 234 pp. |
| 言語 | ENG |
| ニュース番号 | <703-349> |
解説
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.