Optimization of Manufacturing Systems Using the Internet of Things
- 3h 20m
- Fei Tao, Yingfeng Zhang
- Elsevier Science and Technology Books, Inc.
Optimization of Manufacturing Systems Using the Internet of Things extends 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
Graduate students and researchers in manufacturing engineering and operations management; operations managers, control engineers, systems engineers at large manufacturers
About the Authors
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 Engineering, Beihang University, Beijing, China. His research interests are service-oriented intelligent manufacturing, manufacturing service management and optimization, green and sustainable manufacturing.
In this Book
Overview of IoT-Enabled Manufacturing System
Real-Time and Multisource Manufacturing Information Sensing System
IoT-Enabled Smart Assembly Station
Cloud Computing-Based Manufacturing Resources Configuration Method
IoT-Enabled Smart Trolley
Real-Time Key Production Performances Analysis Method
Real-Time Information-Driven Production Scheduling System
IoT-MS Prototype System
Conclusions and Future Works