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.
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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.
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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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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.
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Focuses on quantitative analysis and optimal control of energy efficiency in discrete manufacturing systems Proposes applicable methods to study the issues of energy efficiency quantitative analysis and integrated energy efficiency optimization control Presents new research findings that could serve as benchmark solutions for future research
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GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
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Produktdetaljer

ISBN
9789811544613
Publisert
2020-06-02
Utgiver
Springer Verlag, Singapore; Springer Verlag, Singapore
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, UF, 06, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet

Om bidragsyterne

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.