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MARC 21

Quantitative Analysis and Optimal Control of Energy Efficiency in Discrete Manufacturing System
Tag	Description
020	$a9789811544620
082	$a519
099	$aOnline resource: Springer
100	$aWang, Yan.$eauthor.
245	$aQuantitative Analysis and Optimal Control of Energy Efficiency in Discrete Manufacturing System$h[EBook]$cby Yan Wang, Cheng-Lin Liu, Zhi-Cheng Ji.
250	$a1st ed. 2020.
260	$aSingapore :$bSpringer Singapore :$bImprint: Springer,$c2020.
300	$aXXIV, 272 p. 96 illus., 49 illus. in color.$bonline resource.
336	$atext
338	$aonline resource
505	$aIntroduction -- 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.
520	$aThis 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.
533	$aDigital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format
538	$a - Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
700	$aLiu, Cheng-Lin.$eauthor.
700	$aJi, Zhi-Cheng.$eauthor.
710	$aSpringerLink (Online service)
856	$uhttps://doi.org/10.1007/978-981-15-4462-0