Optimization of physical vapour deposition coating process parameters using genetic algorithm

Optimization of thin film coating parameter is an important task to identify the required output. In the process of physical vapor deposition (PVD), two main issues of the PVD process are cost of manufacturing and customization of the cutting tool properties. In general, a proper choice of the coati...

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Main Author:	Mohammad Jarrah, Mu'ath Ibrahim
Format:	Thesis
Language:	English English
Published:	2014
Subjects:	T Technology (General)
Online Access:	http://eprints.utem.edu.my/id/eprint/14993/1/Optimization%20Of%20Physical%20Vapour%20Deposition%20Coating%20Process%20Parameters%20Using%20Genetic%20Algorithm%2024pages.pdf http://eprints.utem.edu.my/id/eprint/14993/2/Optimization%20of%20physical%20vapour%20deposition%20coating%20process%20parameters%20using%20genetic%20algorithm.pdf
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id	my-utem-ep.14993
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spelling	my-utem-ep.149932022-05-17T09:03:48Z Optimization of physical vapour deposition coating process parameters using genetic algorithm 2014 Mohammad Jarrah, Mu'ath Ibrahim T Technology (General) TA Engineering (General). Civil engineering (General) Optimization of thin film coating parameter is an important task to identify the required output. In the process of physical vapor deposition (PVD), two main issues of the PVD process are cost of manufacturing and customization of the cutting tool properties. In general, a proper choice of the coating process parameters is very important to find the best characteristics of coating and towards less material usage, reduced trial in experiment and less machine maintenance. The aim of this study is to identify optimal PVD coating process parameters. Three process parameters were selected which are nitrogen gas pressure (N2), argon gas pressure (Ar) and turntable speed (TT), while thin film grain size of titanium nitrite (TiN) was selected as an output response. In order to get output result, the three parameters were used to develop a polynomial quadratic equation that was designed using response surface methodology (RSM). Then, in order to optimize the coating process parameters, genetic algorithms (GAs) were used for the optimization work. The results showed that the optimized coating process parameters have lower grain size value compared to the actual experimental data and RSM with (≈6%) ratio and (≈0.03%) ratio, respectively. 2014 Thesis http://eprints.utem.edu.my/id/eprint/14993/ http://eprints.utem.edu.my/id/eprint/14993/1/Optimization%20Of%20Physical%20Vapour%20Deposition%20Coating%20Process%20Parameters%20Using%20Genetic%20Algorithm%2024pages.pdf text en public http://eprints.utem.edu.my/id/eprint/14993/2/Optimization%20of%20physical%20vapour%20deposition%20coating%20process%20parameters%20using%20genetic%20algorithm.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=92149 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering Mohamad Jaya, Abdul Syukor
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Mohamad Jaya, Abdul Syukor
topic	T Technology (General) T Technology (General)
spellingShingle	T Technology (General) T Technology (General) Mohammad Jarrah, Mu'ath Ibrahim Optimization of physical vapour deposition coating process parameters using genetic algorithm
description	Optimization of thin film coating parameter is an important task to identify the required output. In the process of physical vapor deposition (PVD), two main issues of the PVD process are cost of manufacturing and customization of the cutting tool properties. In general, a proper choice of the coating process parameters is very important to find the best characteristics of coating and towards less material usage, reduced trial in experiment and less machine maintenance. The aim of this study is to identify optimal PVD coating process parameters. Three process parameters were selected which are nitrogen gas pressure (N2), argon gas pressure (Ar) and turntable speed (TT), while thin film grain size of titanium nitrite (TiN) was selected as an output response. In order to get output result, the three parameters were used to develop a polynomial quadratic equation that was designed using response surface methodology (RSM). Then, in order to optimize the coating process parameters, genetic algorithms (GAs) were used for the optimization work. The results showed that the optimized coating process parameters have lower grain size value compared to the actual experimental data and RSM with (≈6%) ratio and (≈0.03%) ratio, respectively.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohammad Jarrah, Mu'ath Ibrahim
author_facet	Mohammad Jarrah, Mu'ath Ibrahim
author_sort	Mohammad Jarrah, Mu'ath Ibrahim
title	Optimization of physical vapour deposition coating process parameters using genetic algorithm
title_short	Optimization of physical vapour deposition coating process parameters using genetic algorithm
title_full	Optimization of physical vapour deposition coating process parameters using genetic algorithm
title_fullStr	Optimization of physical vapour deposition coating process parameters using genetic algorithm
title_full_unstemmed	Optimization of physical vapour deposition coating process parameters using genetic algorithm
title_sort	optimization of physical vapour deposition coating process parameters using genetic algorithm
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Manufacturing Engineering
publishDate	2014
url	http://eprints.utem.edu.my/id/eprint/14993/1/Optimization%20Of%20Physical%20Vapour%20Deposition%20Coating%20Process%20Parameters%20Using%20Genetic%20Algorithm%2024pages.pdf http://eprints.utem.edu.my/id/eprint/14993/2/Optimization%20of%20physical%20vapour%20deposition%20coating%20process%20parameters%20using%20genetic%20algorithm.pdf
_version_	1747833856006815744

Optimization of physical vapour deposition coating process parameters using genetic algorithm

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