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

Häftad, Engelska, 2021

AvYan Wang,Cheng-Lin Liu,Zhi-Cheng Ji

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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.

Produktinformation

Utgivningsdatum2021-06-02
Mått155 x 235 x 17 mm
Vikt452 g
FormatHäftad
SpråkEngelska
Antal sidor272
FörlagSpringer Verlag, Singapore
ISBN9789811544644

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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.

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.

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