Quantitative Analysis and Optimal Control of Energy Efficiency in Discrete Manufacturing System -  Zhi-Cheng Ji,  Cheng-Lin Liu,  Yan Wang

Quantitative Analysis and Optimal Control of Energy Efficiency in Discrete Manufacturing System (eBook)

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2020 | 1st ed. 2020
XXIV, 272 Seiten
Springer Singapore (Verlag)
978-981-15-4462-0 (ISBN)
Systemvoraussetzungen
149,79 inkl. MwSt
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This book provides energy efficiency quantitative analysis and optimal methods for discrete manufacturing systems from the perspective of global optimization. In order to analyze and optimize energy efficiency for discrete manufacturing systems, it uses real-time access to energy consumption information and models of the energy consumption, and constructs an energy efficiency quantitative index system. Based on the rough set and analytic hierarchy process, it also proposes a principal component quantitative analysis and a combined energy efficiency quantitative analysis. 
 
In turn, the book addresses the design and development of quantitative analysis systems. To save energy consumption on the basis of energy efficiency analysis, it presents several optimal control strategies, including one for single-machine equipment, an integrated approach based on RWA-MOPSO, and one for production energy efficiency based on a teaching and learning optimal algorithm. Given its scope, the book offers a valuable guide for students, teachers, engineers and researchers in the field of discrete manufacturing systems.



Yan Wang received her Ph.D. degree from Nanjing University of Science and Technology, China, in 2006. She is currently a professor at the School of Internet of Things Engineering, Jiangnan University, China. Her research interests include Energy-Efficient Control of Complex Manufacturing System, Industrial Networked System, and Evolutionary Computing.

Cheng-Lin Liu received his Ph.D. degree from Southeast University, China, in 2008. He is currently a professor at the School of Internet of Things Engineering, Jiangnan University, China. His research interests include Coordination Control of Multi-agent Systems and Distributed Control of Networked Systems.

Zhi-Cheng Ji received his Ph.D. degree from China University of Mining and Technology, China, in 2004. He is currently the vice president of Jiangnan University.


This book provides energy efficiency quantitative analysis and optimal methods for discrete manufacturing systems from the perspective of global optimization. In order to analyze and optimize energy efficiency for discrete manufacturing systems, it uses real-time access to energy consumption information and models of the energy consumption, and constructs an energy efficiency quantitative index system. Based on the rough set and analytic hierarchy process, it also proposes a principal component quantitative analysis and a combined energy efficiency quantitative analysis.  In turn, the book addresses the design and development of quantitative analysis systems. To save energy consumption on the basis of energy efficiency analysis, it presents several optimal control strategies, including one for single-machine equipment, an integrated approach based on RWA-MOPSO, and one for production energy efficiency based on a teaching and learning optimal algorithm. Given its scope, the book offers a valuable guide for students, teachers, engineers and researchers in the field of discrete manufacturing systems.
Erscheint lt. Verlag 1.6.2020
Zusatzinfo XXIV, 272 p. 96 illus., 49 illus. in color.
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Mathematik Angewandte Mathematik
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Naturwissenschaften
Technik Elektrotechnik / Energietechnik
Technik Maschinenbau
Wirtschaft Betriebswirtschaft / Management Logistik / Produktion
Schlagworte Discrete manufacturing system • Energy Consumption • Energy efficiency optimization • Optimal control strategy • Quantitative Analysis
ISBN-10 981-15-4462-X / 981154462X
ISBN-13 978-981-15-4462-0 / 9789811544620
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