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Transforming Industries: Capturing the Potential of IIoT and ML in the Era of Industry 5.0.
・ISBN 978-1-032-88447-9 hard GB£ 145.99
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| 著者・編者 | Kalra, Ashima / Rani, Sita / Kumar, Ravinder / Elngar, Ahmed A. (eds.), |
|---|---|
| シリーズ | (Intelligent Manufacturing and Industrial Engineering) |
| 出版社 | (CRC Press, UK) |
| 出版年月 | 2025 |
| ページ数 | 336 pp. |
| 言語 | ENG |
| ニュース番号 | <A04-49191> |
解説
The rapid convergence of the industrial internet of things (IIoT) and machine learning (ML) is propelling us into a new era known as Industry 5.0. This era is defined by unparalleled levels of automation, customization, and sustainability. Despite these advancements, there is a noticeable absence of comprehensive resources that offer a complete understanding of these transformative technologies and their practical applications across various industrial sectors. Transforing Industries: Capturing the Potential of IIoT and ML in the Era of Industry 5.0 aims to fill the void by providing a timely and relevant guide that explores the theoretical foundations of the technologies while also presenting real-world case studies and best practices.
This comprehensive text discusses the profound impact of the IIoT and ML on various sectors, including manufacturing, supply chain management, and energy production. It provides a thorough examination of the opportunities and obstacles associated with these cutting-edge technologies. Through real-world case studies and success stories, readers gain insight into how industry leaders have successfully leveraged IIoT and ML solutions to optimize operational efficiency, foster innovation, and achieve unparalleled excellence. Practical strategies and detailed guidelines are also offered to facilitate the seamless integration of these technologies into existing workflows, empowering businesses to navigate the complexities of digital transformation with confidence. The focus of this publication also extends to future trends and potential disruptors in the era of Industry 5.0, equipping readers with the knowledge needed to anticipate and adapt to emerging challenges. Furthermore, the exploration of how IIoT and ML can streamline resource allocation, minimize waste, and promote sustainable practices underscores the alignment of technological advancements with corporate, environmental, and social responsibilities.
By equipping industry leaders, professionals, and entrepreneurs with actionable insights, this book will empower businesses to stay ahead of the curve, foster innovation, optimize resource utilization, and ultimately gain a competitive advantage in the ever-evolving manufacturing landscape.