Optimization Of Manufacturing Systems Using The Internet Of Things by Yingfeng ZhangOptimization Of Manufacturing Systems Using The Internet Of Things by Yingfeng Zhang

Optimization Of Manufacturing Systems Using The Internet Of Things

byYingfeng Zhang, Fei Tao

Paperback | October 25, 2016

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Optimization of Manufacturing Systems Using the Internet of Thingsextends the IoT (Internet of Things) into the manufacturing field to develop an IoMT (Internet of Manufacturing Things) architecture with real-time traceability, visibility, and interoperability in production planning, execution, and control. This book is essential reading for anyone interested in the optimization and control of an intelligent manufacturing system.

As modern manufacturing shop-floors can create bottlenecks in the capturing and collection of real-time field information, and because paper-based manual systems are time-consuming and prone to errors, this book helps readers understand how to alleviate these issues, assisting them in their decision-making on shop-floors.

  • Includes case studies in implementing IoTs for data acquisition, monitoring, and assembly in manufacturing.
  • Helps manufacturers to tackle the growing complexities and uncertainties of manufacturing systems in globalized business environments
  • Acts as an introduction to using IoT for readers across industrial and manufacturing engineering
Yingfeng Zhang is a professor at the department of Industrial Engineering of the Northwestern Polytechnical University, China. Currently, his research interests are the Internet of Manufacturing Things (IoMT) and real-time data driven production optimization.Fei Tao is a Professor at the School of Automation Science and Electrical Engi...
Title:Optimization Of Manufacturing Systems Using The Internet Of ThingsFormat:PaperbackDimensions:226 pages, 8.75 × 6.35 × 0.68 inPublished:October 25, 2016Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0128099100

ISBN - 13:9780128099100

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Table of Contents

1. Introduction
2. Overview of IoMT
3. Real-time and multi-source manufacturing information perception
4. IoT-enabled smart assembly station
5. Cloud computing based manufacturing resources configuration method
6. Real-time information-driven production-scheduling system
7. IoT-enabled smart material handling
8. Real-time key production performances monitor method
9. IoMTprototype system
10. Conclusions and future works