Overview
- Provides a bio-inspired control approach for intelligent manufacturing systems
- Includes multiple product control models with extensive applications
- Offers several production optimization approaches based on neuroendocrine-immune regulatory and hormone-regulation mechanisms
Part of the book series: Research on Intelligent Manufacturing (REINMA)
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Table of contents (6 chapters)
Keywords
About this book
It offers a valuable resource for graduate students, researchers and engineers in the fields of production management, manufacturing system control and related areas.
Authors and Affiliations
About the authors
Dr. Kun Zheng is a lecturer at School of Automotive and Rail Transit, Nanjing Institute of Technology, and a researcher at Jiangsu Key Laboratory of Advanced Numerical Control Technology. Dr. Zheng received his PhD degree at Nanjing University of Aeronautics and Astronautics (NUAA). Dr. Zheng’s research interests include Intelligent Manufacturing System, Intelligent Equipment and Information System Integration.
Dr. Wenbin Gu is a lecturer at the College of Mechanical and Electrical Engineering, Hohai University Changzhou Campus, China. He has received his PhD degree at Nanjing University of Aeronautics and Astronautics (NUAA). And then, he studied at the University of Illinois in Chicago for one year as a visiting scholar. His research interests include Sustainable Manufacturing System, Intelligent Manufacturing System and Automation.
Bibliographic Information
Book Title: Adaptive Control of Bio-Inspired Manufacturing Systems
Authors: Dunbing Tang, Kun Zheng, Wenbin Gu
Series Title: Research on Intelligent Manufacturing
DOI: https://doi.org/10.1007/978-981-15-3445-4
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-15-3444-7Published: 28 February 2020
Softcover ISBN: 978-981-15-3447-8Published: 28 February 2021
eBook ISBN: 978-981-15-3445-4Published: 27 February 2020
Series ISSN: 2523-3386
Series E-ISSN: 2523-3394
Edition Number: 1
Number of Pages: IX, 128
Number of Illustrations: 20 b/w illustrations, 43 illustrations in colour
Topics: Control and Systems Theory, Artificial Intelligence, Manufacturing, Machines, Tools, Processes, Quality Control, Reliability, Safety and Risk