Overview
- Presents innovative Big Data analytics and deep learning technologies for intelligent manufacturing
- Illustrates design details of algorithms and methodologies using industrial case studies
- Offers a valuable resource for researchers and engineers in this field
Part of the book series: Springer Series in Advanced Manufacturing (SSAM)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers.
Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress.
This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.
Editors and Affiliations
About the editors
Prof. Weidong Li is a full professor in manufacturing, Coventry University (UK). Professor Li has more than twenty years’ experiences in computer aided design, manufacturing informatics, smart manufacturing and sustainable manufacturing. His research has been sponsored by a number of research and development projects from the UK EPSRC, European Commission and European industries such as Jaguar Land Rover, Airbus, Rolls-Royce, Sandvik, etc. In the research areas, he has published four books and around 200 research papers in international journals and conferences.
Dr Yuchen Liang is a lecturer from Coventry University. Dr Liang has gotten his PhD degree from Coventry University from Automotive and Mechanical Engineering. His research areas are data driven smart manufacturing and cyber-physical manufacturing systems. His research works have been sponsored by the European Commission and the Innovate UK.Dr Sheng Wang is a senior researcher in manufacturing, Coventry University, UK. Dr Wang has gotten her PhD degree from Queen Mary University of London from Computer Science and Electronic Engineering. In the past five years, Dr Wang has participated in a number of European Commission-sponsored projects in smart manufacturing.
Bibliographic Information
Book Title: Data Driven Smart Manufacturing Technologies and Applications
Editors: Weidong Li, Yuchen Liang, Sheng Wang
Series Title: Springer Series in Advanced Manufacturing
DOI: https://doi.org/10.1007/978-3-030-66849-5
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-66848-8Published: 21 February 2021
Softcover ISBN: 978-3-030-66851-8Published: 22 February 2022
eBook ISBN: 978-3-030-66849-5Published: 20 February 2021
Series ISSN: 1860-5168
Series E-ISSN: 2196-1735
Edition Number: 1
Number of Pages: IX, 218
Number of Illustrations: 13 b/w illustrations, 130 illustrations in colour
Topics: Manufacturing, Machines, Tools, Processes, Robotics, Simulation and Modeling, Mechanical Engineering