Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling

Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling

Machining of hardened steel at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality and cutting tool life. Thus, predicting the temperature in early stage becomes utmost importance. This research presents a neural network model for predicting the cutt...

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Main Authors: Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Suprianto, M.Y, Riza, Muhammad
Format: Article
Language:English
Published: Trans Tech Publications 2012
Subjects:
T Technology (General)
Online Access:http://irep.iium.edu.my/30262/
http://irep.iium.edu.my/30262/
http://irep.iium.edu.my/30262/
http://irep.iium.edu.my/30262/1/AMR.576.91.pdf
id iium-30262
recordtype eprints
spelling iium-302622013-09-20T02:49:02Z http://irep.iium.edu.my/30262/ Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Suprianto, M.Y Riza, Muhammad T Technology (General) Machining of hardened steel at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality and cutting tool life. Thus, predicting the temperature in early stage becomes utmost importance. This research presents a neural network model for predicting the cutting temperature in the CNC end milling process. The Artificial Neural Network (ANN) was applied as an effective tool for modeling and predicting the cutting temperature. A set of sparse experimental data for finish end milling on AISI H13 at hardness of 48 HRC have been conducted to measure the cutting temperature. The artificial neural network (ANN) was applied to predict the cutting temperature. Twenty hidden layer has been used with feed forward back propagation hierarchical neural networks were designed with Matlab2009b Neural Network Toolbox. The results show a high correlation between the predicted and the observed temperature which indicates the validity of the models. Trans Tech Publications 2012 Article PeerReviewed application/pdf en http://irep.iium.edu.my/30262/1/AMR.576.91.pdf Al Hazza, Muataz Hazza Faizi and Adesta, Erry Yulian Triblas and Suprianto, M.Y and Riza, Muhammad (2012) Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling. Advanced Materials Research, 576. pp. 91-94. ISSN 1022-6680 http://www.scientific.net/AMR.576.91 10.4028/www.scientific.net/AMR.576.91
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic T Technology (General)
spellingShingle T Technology (General)
Al Hazza, Muataz Hazza Faizi
Adesta, Erry Yulian Triblas
Suprianto, M.Y
Riza, Muhammad
Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling
description Machining of hardened steel at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality and cutting tool life. Thus, predicting the temperature in early stage becomes utmost importance. This research presents a neural network model for predicting the cutting temperature in the CNC end milling process. The Artificial Neural Network (ANN) was applied as an effective tool for modeling and predicting the cutting temperature. A set of sparse experimental data for finish end milling on AISI H13 at hardness of 48 HRC have been conducted to measure the cutting temperature. The artificial neural network (ANN) was applied to predict the cutting temperature. Twenty hidden layer has been used with feed forward back propagation hierarchical neural networks were designed with Matlab2009b Neural Network Toolbox. The results show a high correlation between the predicted and the observed temperature which indicates the validity of the models.
format Article
author Al Hazza, Muataz Hazza Faizi
Adesta, Erry Yulian Triblas
Suprianto, M.Y
Riza, Muhammad
author_facet Al Hazza, Muataz Hazza Faizi
Adesta, Erry Yulian Triblas
Suprianto, M.Y
Riza, Muhammad
author_sort Al Hazza, Muataz Hazza Faizi
title Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling
title_short Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling
title_full Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling
title_fullStr Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling
title_full_unstemmed Prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened H-13 steel in CNC end milling
title_sort prediction of cutting temperatures by using back propagation neural network modeling when cutting hardened h-13 steel in cnc end milling
publisher Trans Tech Publications
publishDate 2012
url http://irep.iium.edu.my/30262/
http://irep.iium.edu.my/30262/
http://irep.iium.edu.my/30262/
http://irep.iium.edu.my/30262/1/AMR.576.91.pdf
first_indexed 2023-09-18T20:44:25Z
last_indexed 2023-09-18T20:44:25Z
_version_ 1777409579256119296

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