Customized Production Through 3D Printing in Cloud Manufacturing
Language: English
Published by Elsevier, 2022
- Softcover
- New

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- Title
- Customized Production Through 3D Printing in Cloud Manufacturing
- Author
- Zhang, Lin; Zhou, Longfei; Xiao, Luo
- Publisher
- Elsevier
- Publication year
- 2022
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0128235012
- ISBN 13
- 9780128235010
Customized Production Through 3D Printing in Cloud Manufacturing explains how to combine the latest cloud manufacturing and additive manufacturing technology to find innovative solutions to important problems in research and industry.
The manufacturing industry strives constantly to improve levels of product personalization for its customers, who have become increasingly demanding in this respect in recent decades. Among the tools currently growing in use in the industry, there is great potential to address this demand. Cloud manufacturing maps manufacturing resources and capabilities to the cloud, adding the capacity to gather decentralized manufacturing resources and use manufacturing services on-demand, and 3D printing provides strong support for truly individualized manufactured components.
This is the first book to cover the whole lifecycle of 3D printing services in a cloud environment, including topics like: cloud servitization of 3D printers, 3D printing model design, supply-demand matching and scheduling, on-demand using and pricing, printing monitoring in cloud, and printing service evaluation. With a systematic introduction to this promising manufacturing paradigm, as well as coverage of models and service management to practical applications, this book will meet the needs of a broad range of researchers as well as practitioners.
- Provides readers with a unique combined technical overview of two rapidly developing technologies and how they interact in a modern manufacturing system
- Explores important challenges to security and privacy posed by these new technologies
- Draws on valuable knowledge of how these technologies have been applied in innovative industry settings
"Synopsis" may belong to another edition of this title.
About the Author
Longfei Zhou is currently a postdoc associate in the Carl E. Ravin Advanced Imaging Laboratories (RAI Labs) at Duke University. His research interests include cloud manufacturing, scheduling, modeling and simulation, and computer vision. Dr. Zhou received his Ph.D. degree in 2018 from Beihang University where he studied the dynamic scheduling problem in cloud manufacturing and proposed the simulation-based dynamic scheduling method to overcome uncertainties. In January 2019, Dr. Zhou joined MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) as a postdoc to study reinforcement learning-based scheduling and logistics scheduling problems. In October 2020, he joined Duke University as a postdoc to do machine learning-based medical imaging analysis.
Xiao Luo is a researcher in the Dept of Information and Communication Engineering at Beihang University, China. His research interests are focused on cloud manufacturing.
"About the title" may belong to another edition of this title.
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