APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS

APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS

Artificial neural networks, so far, have not been used for designing modular cells. Therefore, Self-organizing neural network (SONN) is used in the present research to design minicell-based manufacturing system. Two previously developed methods were studied and implemented using SONN model. Results...

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Bibliographic Details
Main Author: Goyal, Arvind
Format: Others
Published: UKnowledge 2008
Subjects:
Cellular Manufacturing|Minicell|Mass customization|Material Handling|Self-Organizing neural network
Online Access:http://uknowledge.uky.edu/gradschool_theses/508
http://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1512&context=gradschool_theses
id ndltd-uky.edu-oai-uknowledge.uky.edu-gradschool_theses-1512
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spelling ndltd-uky.edu-oai-uknowledge.uky.edu-gradschool_theses-15122015-04-11T05:05:35Z APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS Goyal, Arvind Artificial neural networks, so far, have not been used for designing modular cells. Therefore, Self-organizing neural network (SONN) is used in the present research to design minicell-based manufacturing system. Two previously developed methods were studied and implemented using SONN model. Results obtained are compared with previous results to analyze the effectiveness of SONN in designing minicells. A new method is then developed with the objective to design minicells more effectively and efficiently. Results of all three methods are compared using machine-count and materialhandling as performance measuring criteria to find out the best method 2008-01-01T08:00:00Z text application/pdf http://uknowledge.uky.edu/gradschool_theses/508 http://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1512&context=gradschool_theses University of Kentucky Master's Theses UKnowledge Cellular Manufacturing|Minicell|Mass customization|Material Handling|Self-Organizing neural network
collection NDLTD
format Others
sources NDLTD
topic Cellular Manufacturing|Minicell|Mass customization|Material Handling|Self-Organizing neural network
spellingShingle Cellular Manufacturing|Minicell|Mass customization|Material Handling|Self-Organizing neural network
Goyal, Arvind
APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS
description Artificial neural networks, so far, have not been used for designing modular cells. Therefore, Self-organizing neural network (SONN) is used in the present research to design minicell-based manufacturing system. Two previously developed methods were studied and implemented using SONN model. Results obtained are compared with previous results to analyze the effectiveness of SONN in designing minicells. A new method is then developed with the objective to design minicells more effectively and efficiently. Results of all three methods are compared using machine-count and materialhandling as performance measuring criteria to find out the best method
author Goyal, Arvind
author_facet Goyal, Arvind
author_sort Goyal, Arvind
title APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS
title_short APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS
title_full APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS
title_fullStr APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS
title_full_unstemmed APPLICATION OF ARTIFICIAL NEURAL NETWORK TECHNIQUES FOR DESIGN OF MODULAR MINICELL CONFIGURATIONS
title_sort application of artificial neural network techniques for design of modular minicell configurations
publisher UKnowledge
publishDate 2008
url http://uknowledge.uky.edu/gradschool_theses/508
http://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1512&context=gradschool_theses
work_keys_str_mv AT goyalarvind applicationofartificialneuralnetworktechniquesfordesignofmodularminicellconfigurations
_version_ 1716801228799737856

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