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Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network

Organized by School of Materials Engineering & Sustainable Engineering Research Cluster, 1st - 2nd December 2009 at Putra Brasmana Hotel, Kuala Perlis, Perlis.

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Bibliographic Details
Main Authors: Yan P., Detak, Syarif Junaidi, S Djalil, Rizauddin, Ramli
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis 2010
Subjects:
Ti-6Al-4V alloys
Tensile properties
Feed Forward Neural Network
Alloys
Prediction system
Heat treatment
Alloys > Testing
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/7490
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spelling my.unimap-74902010-01-12T03:43:51Z Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network Yan P., Detak Syarif Junaidi, S Djalil Rizauddin, Ramli Ti-6Al-4V alloys Tensile properties Feed Forward Neural Network Alloys Prediction system Heat treatment Alloys -- Testing Organized by School of Materials Engineering & Sustainable Engineering Research Cluster, 1st - 2nd December 2009 at Putra Brasmana Hotel, Kuala Perlis, Perlis. A prediction system of tensile properties for heat treated Ti-6Al-4V alloys has been developed. Two different heat treatment processes are conducted to the Ti-6Al-4V alloys, i.e. Solution Treatment with Aging (STA) and annealing process. Different cooling rates have been adjusted to determine the effect on the tensile properties. Ultimate Tensile Strength (UTS), Yield Stress (YS) and Elongation (E) are the kinds of tensile properties which set as the output of prediction system. STA and the annealing process are heat treatment processes which are set as input of the system in combination with annealing temperature and strain rates. In order to develop the prediction system, this study adopts Artificial Neural Network (ANN) which can be used to solve the non-linear correlation problems. Feed Forward Back Propagation (FFBP) as the variety of ANN is adjusted with two types of learning algorithms, that is Gradient Descent with Momentum (GDM) and Lavenberg Marquardt (LM). This study uses Normalized Root Mean Square Error (NRMSE) and Coefficient Correlation (R) to identify the performance of the network. 2010-01-12T03:41:42Z 2010-01-12T03:41:42Z 2009-12-01 Working Paper p.1-5 http://hdl.handle.net/123456789/7490 en Proceedings of the Malaysian Metallurgical Conference '09 (MMC'09) Universiti Malaysia Perlis
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Ti-6Al-4V alloys
Tensile properties
Feed Forward Neural Network
Alloys
Prediction system
Heat treatment
Alloys -- Testing
spellingShingle Ti-6Al-4V alloys
Tensile properties
Feed Forward Neural Network
Alloys
Prediction system
Heat treatment
Alloys -- Testing
Yan P., Detak
Syarif Junaidi, S Djalil
Rizauddin, Ramli
Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network
description Organized by School of Materials Engineering & Sustainable Engineering Research Cluster, 1st - 2nd December 2009 at Putra Brasmana Hotel, Kuala Perlis, Perlis.
format Working Paper
author Yan P., Detak
Syarif Junaidi, S Djalil
Rizauddin, Ramli
author_facet Yan P., Detak
Syarif Junaidi, S Djalil
Rizauddin, Ramli
author_sort Yan P., Detak
title Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network
title_short Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network
title_full Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network
title_fullStr Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network
title_full_unstemmed Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network
title_sort prediction the effect of heat treatment in tensile properties of ti-6al-4v alloys using artificial neural network
publisher Universiti Malaysia Perlis
publishDate 2010
url http://dspace.unimap.edu.my/xmlui/handle/123456789/7490
_version_ 1643788839660027904
score 13.159267

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