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Application of fuzzy rule-based model to predict TiAlN coatings roughness

In this work, an approach for predicting the roughness of Titanium Aluminum Nitride (TiAlN) coatings using fuzzy ruled-based model was discussed. TiAlN coatings were produced using magnetron sputtering process. Tungsten carbide (WC) was selected as the substrate and titanium alloy was used as the ma...

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Main Authors: Mohamad Jaya, Abdul Syukor, Muhamad, Mohd. Razali, Abd. Rahman, Md. Nizam, Mohd. Hashim, Siti Zaiton
Format: Article
Published: 2012
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://eprints.utm.my/id/eprint/46617/
http://dx.doi.org/10.4028/www.scientific.net/AMM.110-116.1072
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spelling my.utm.466172017-09-17T06:46:15Z http://eprints.utm.my/id/eprint/46617/ Application of fuzzy rule-based model to predict TiAlN coatings roughness Mohamad Jaya, Abdul Syukor Muhamad, Mohd. Razali Abd. Rahman, Md. Nizam Mohd. Hashim, Siti Zaiton TJ Mechanical engineering and machinery In this work, an approach for predicting the roughness of Titanium Aluminum Nitride (TiAlN) coatings using fuzzy ruled-based model was discussed. TiAlN coatings were produced using magnetron sputtering process. Tungsten carbide (WC) was selected as the substrate and titanium alloy was used as the material to coat the cutting tool. The sputtering power, substrate bias voltage and substrate temperature were selected as the input variables while roughness of the TiAlN coatings was considered as the response variable. A statistical design of experiments method known as centre cubic design (CCD) was selected to collect the data for developing the fuzzy rules. The prediction performances of the fuzzy rule-based model with respect to percentage error, mean squared error (MSE), co-efficient determination (R2) and model accuracy were compared with the response surface regression model (RSM). The result shown that the fuzzy rule-based model has much better predicting capability compared to the RSM. 2012 Article PeerReviewed Mohamad Jaya, Abdul Syukor and Muhamad, Mohd. Razali and Abd. Rahman, Md. Nizam and Mohd. Hashim, Siti Zaiton (2012) Application of fuzzy rule-based model to predict TiAlN coatings roughness. Applied Mechanics And Materials, 110-11 . ISSN 1660-9336 http://dx.doi.org/10.4028/www.scientific.net/AMM.110-116.1072
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Mohamad Jaya, Abdul Syukor
Muhamad, Mohd. Razali
Abd. Rahman, Md. Nizam
Mohd. Hashim, Siti Zaiton
Application of fuzzy rule-based model to predict TiAlN coatings roughness
description In this work, an approach for predicting the roughness of Titanium Aluminum Nitride (TiAlN) coatings using fuzzy ruled-based model was discussed. TiAlN coatings were produced using magnetron sputtering process. Tungsten carbide (WC) was selected as the substrate and titanium alloy was used as the material to coat the cutting tool. The sputtering power, substrate bias voltage and substrate temperature were selected as the input variables while roughness of the TiAlN coatings was considered as the response variable. A statistical design of experiments method known as centre cubic design (CCD) was selected to collect the data for developing the fuzzy rules. The prediction performances of the fuzzy rule-based model with respect to percentage error, mean squared error (MSE), co-efficient determination (R2) and model accuracy were compared with the response surface regression model (RSM). The result shown that the fuzzy rule-based model has much better predicting capability compared to the RSM.
format Article
author Mohamad Jaya, Abdul Syukor
Muhamad, Mohd. Razali
Abd. Rahman, Md. Nizam
Mohd. Hashim, Siti Zaiton
author_facet Mohamad Jaya, Abdul Syukor
Muhamad, Mohd. Razali
Abd. Rahman, Md. Nizam
Mohd. Hashim, Siti Zaiton
author_sort Mohamad Jaya, Abdul Syukor
title Application of fuzzy rule-based model to predict TiAlN coatings roughness
title_short Application of fuzzy rule-based model to predict TiAlN coatings roughness
title_full Application of fuzzy rule-based model to predict TiAlN coatings roughness
title_fullStr Application of fuzzy rule-based model to predict TiAlN coatings roughness
title_full_unstemmed Application of fuzzy rule-based model to predict TiAlN coatings roughness
title_sort application of fuzzy rule-based model to predict tialn coatings roughness
publishDate 2012
url http://eprints.utm.my/id/eprint/46617/
http://dx.doi.org/10.4028/www.scientific.net/AMM.110-116.1072
_version_ 1643652088495865856
score 13.211869

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