书目名称 | Industry 4.0 Driven Manufacturing Technologies | 编辑 | Ajay Kumar,Parveen Kumar,Yang Liu | 视频video | | 概述 | Provides case studies showing solutions from industry and society.Integrates Industry 4.0 tools, e.g., digital twins, artificial intelligence, nature-inspired algorithms, and the IoT.Bridges the gap b | 丛书名称 | Springer Series in Advanced Manufacturing | 图书封面 |  | 描述 | .This book is a comprehensive guide to the latest advancements in manufacturing, adopting an Industry 4.0 approach. It covers the core principles of big data informatics, digital twin technology, artificial intelligence, and machine learning strategies. Readers will gain insights into the realm of cyber-physical intelligent systems in production, the role of blockchain, and the significance of information and communication technology...With a focus on real-time monitoring and data acquisition, the book offers practical solutions for online error troubleshooting in manufacturing systems. It explores a wide range of Industry 4.0-based applied manufacturing technologies and addresses the challenges posed by the dynamic market of production...Recognizing the lack of a cohesive resource on manufacturing advancements within the context of Industry 4.0, the authors have taken the initiative to compile this valuable knowledge from domain experts. Their goal is to disseminate these insights with this book...The book will be beneficial to various stakeholders, including industries, professionals, academics, research scholars, senior graduate students, and those in the field of human healthca | 出版日期 | Book 2024 | 关键词 | Intelligent Manufacturing; Industry 4; 0; Digital Twin; Artificial Intelligence; Internet of things; Cyber | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-68271-1 | isbn_softcover | 978-3-031-68273-5 | isbn_ebook | 978-3-031-68271-1Series ISSN 1860-5168 Series E-ISSN 2196-1735 | issn_series | 1860-5168 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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