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.
Cuprins
Introduction.- Quantitative analysis of real-time access to energy consumption information.- Energy consumption integration model for discrete manufacturing systems.- Construction of energy efficiency quantitative index system for discrete manufacturing system.- Combined energy efficiency quantitative analysis based on rough Set and analytic hierarchy process.- Energy efficiency quantitative analysis based on principal component analysis.- Design and development of quantitative analysis systems.- Energy saving optimization control of single machine equipment.- Integrated Energy Efficiency Optimization Control Based on RWA-MOPSO.- Production energy efficiency optimization control based on teaching and learning algorithm.
Despre autor
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.
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