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Warpage optimization of a name card holder using neural network model

Injection molding has become widely process that used in plastic manufacturing. To produce high quality product, it has to consider the process condition. In this study, optimum parameters for injection molding of a name card holder are determined. Finite element software MoldFlow, statistical desig...

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Main Author: Ahmad Amiruddin, Rosdi
Format: Undergraduates Project Papers
Language:English
Published: 2009
Subjects:
TP Chemical technology
Online Access:http://umpir.ump.edu.my/id/eprint/1172/1/Warpage%20optimization%20of%20a%20name%20card%20holder%20using%20neural%20network%20model.pdf
http://umpir.ump.edu.my/id/eprint/1172/
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spelling my.ump.umpir.11722022-03-24T02:32:04Z http://umpir.ump.edu.my/id/eprint/1172/ Warpage optimization of a name card holder using neural network model Ahmad Amiruddin, Rosdi TP Chemical technology Injection molding has become widely process that used in plastic manufacturing. To produce high quality product, it has to consider the process condition. In this study, optimum parameters for injection molding of a name card holder are determined. Finite element software MoldFlow, statistical design of experiment and artificial neural network are used in finding optimum value. The process parameter influencing warpage is determined using finite element software based on data using full factorial design. By exploiting finite element analysis result, a predictive model using artificial neural network is created. Optimum value is determined by comparing result by using finite element analysis and optimization using artificial neural network and choose the smallest percentage of error. 2009-11 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/1172/1/Warpage%20optimization%20of%20a%20name%20card%20holder%20using%20neural%20network%20model.pdf Ahmad Amiruddin, Rosdi (2009) Warpage optimization of a name card holder using neural network model. Faculty of Mechanical Engineering, UNIVERSITI MALAYSIA PAHANG.
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
Ahmad Amiruddin, Rosdi
Warpage optimization of a name card holder using neural network model
description Injection molding has become widely process that used in plastic manufacturing. To produce high quality product, it has to consider the process condition. In this study, optimum parameters for injection molding of a name card holder are determined. Finite element software MoldFlow, statistical design of experiment and artificial neural network are used in finding optimum value. The process parameter influencing warpage is determined using finite element software based on data using full factorial design. By exploiting finite element analysis result, a predictive model using artificial neural network is created. Optimum value is determined by comparing result by using finite element analysis and optimization using artificial neural network and choose the smallest percentage of error.
format Undergraduates Project Papers
author Ahmad Amiruddin, Rosdi
author_facet Ahmad Amiruddin, Rosdi
author_sort Ahmad Amiruddin, Rosdi
title Warpage optimization of a name card holder using neural network model
title_short Warpage optimization of a name card holder using neural network model
title_full Warpage optimization of a name card holder using neural network model
title_fullStr Warpage optimization of a name card holder using neural network model
title_full_unstemmed Warpage optimization of a name card holder using neural network model
title_sort warpage optimization of a name card holder using neural network model
publishDate 2009
url http://umpir.ump.edu.my/id/eprint/1172/1/Warpage%20optimization%20of%20a%20name%20card%20holder%20using%20neural%20network%20model.pdf
http://umpir.ump.edu.my/id/eprint/1172/
_version_ 1729703415167057920
score 13.211869

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