Energy efficiency in manufacturing systems

Energy efficiency in manufacturing systems / Sebastian Thiede.

"Energy consumption is of great interest to manufacturing companies. Beyond considering individual processes and machines, the perspective on process chains and factories as a whole holds major potentials for energy efficiency improvements. To exploit these potentials, dynamic interactions of d...

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Bibliographic Details
Main Author: Thiede, Sebastian
Format: eBook
Language:English
Published: Berlin ; New York : Springer, ©2012.
Series:Sustainable production, life cycle engineering and management.
Subjects:
Manufacturing industries > Energy consumption.
BUSINESS & ECONOMICS > Industries > Energy.
SCIENCE > Energy.
TECHNOLOGY & ENGINEERING > Power Resources > General.
Ingénierie.
Manufacturing industries > Energy consumption
Online Access:Click for online access

MARC

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100 1 |a Thiede, Sebastian. 
245 1 0 |a Energy efficiency in manufacturing systems /  |c Sebastian Thiede. 
260 |a Berlin ;  |a New York :  |b Springer,  |c ©2012. 
300 |a 1 online resource (xxii, 198 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file 
347 |b PDF 
490 1 |a Sustainable production, life cycle engineering and management,  |x 2194-0541 
504 |a Includes bibliographical references and index. 
505 0 0 |t Introduction --  |t Theoretical Background --  |t Derivation of Requirements and Methodological Approach --  |t State of Research --  |t Concept Development --  |t Application of Concept --  |t Summary and Outlook. 
505 0 0 |g Part 1.  |t Introduction --  |t Probabilistic Graphical Models and Markov Networks /  |r Roberto Santana and Siddhartha Shakya --  |t A Review of Estimation of Distribution Algorithms and Markov Networks /  |r Siddhartha Shakya and Roberto Santana --  |t MOA -- Markovian Optimisation Algorithm /  |r Siddhartha Shakya and Roberto Santana --  |t DEUM -- Distribution Estimation Using Markov Networks /  |r Siddhartha Shakya, John McCall, Alexander Brownlee and Gilbert Owusu --  |t MN-EDA and the Use of Clique-Based Factorisations in EDAs /  |r Roberto Santana. 
505 0 0 |g Part 2.  |t Theory --  |t Convergence Theorems of Estimation of Distribution Algorithms /  |r Heinz Mühlenbein --  |t Adaptive Evolutionary Algorithm Based on a Cliqued Gibbs Sampling over Graphical Markov Model Structure /  |r Eunice Esther Ponce-de-Leon-Senti and Elva Diaz-Diaz --  |t The Markov Network Fitness Model /  |r Alexander E.I. Brownlee, John A.W. McCall and Siddhartha K. Shakya --  |t Fast Fitness Improvements in Estimation of Distribution Algorithms Using Belief Propagation /  |r Alexander Mendiburu, Roberto Santana and Jose A. Lozano --  |t Continuous Estimation of Distribution Algorithms Based on Factorized Gaussian Markov Networks /  |r Hossein Karshenas, Roberto Santana, Concha Bielza and Pedro Larrañaga --  |t Using Maximum Entropy and Generalized Belief Propagation in Estimation of Distribution Algorithms /  |r Robin Höns. 
505 0 0 |g Part 3.  |t Application --  |t Applications of Distribution Estimation Using Markov Network Modelling (DEUM) /  |r John McCall, Alexander Brownlee and Siddhartha Shakya --  |t Vine Estimation of Distribution Algorithms with Application to Molecular Docking /  |r Marta Soto, Alberto Ochoa, Yasser González-Fernández, Yanely Milanés and Adriel Álvarez, et al. --  |t EDA-RL: EDA with Conditional Random Fields for Solving Reinforcement Learning Problems /  |r Hisashi Handa. 
520 |a "Energy consumption is of great interest to manufacturing companies. Beyond considering individual processes and machines, the perspective on process chains and factories as a whole holds major potentials for energy efficiency improvements. To exploit these potentials, dynamic interactions of different processes as well as auxiliary equipment (e.g. compressed air generation) need to be taken into account. In addition, planning and controlling manufacturing systems require balancing technical, economic and environmental objectives. Therefore, an innovative and comprehensive methodology--with a generic energy flow-oriented manufacturing simulation environment as a core element--is developed and embedded into a step-by-step application cycle. The concept is applied in its entirety to a wide range of case studies such as aluminium die casting, weaving mills, and printed circuit board assembly in order to demonstrate the broad applicability and the benefits that can be achieved"--Provided by publisher 
546 |a English. 
650 0 |a Manufacturing industries  |x Energy consumption. 
650 7 |a BUSINESS & ECONOMICS  |x Industries  |x Energy.  |2 bisacsh 
650 7 |a SCIENCE  |x Energy.  |2 bisacsh 
650 7 |a TECHNOLOGY & ENGINEERING  |x Power Resources  |x General.  |2 bisacsh 
650 7 |a Ingénierie.  |2 eclas 
650 7 |a Manufacturing industries  |x Energy consumption  |2 fast 
758 |i has work:  |a Energy efficiency in manufacturing systems (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCGrvHhRb3JqdHh8kMGq4YK  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Printed edition:  |z 9783642259135 
830 0 |a Sustainable production, life cycle engineering and management. 
856 4 0 |u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=973962  |y Click for online access 
903 |a EBC-AC 
994 |a 92  |b HCD 

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