Enhancement of the machining surface roughness model with cuckoo algorithm

Quality of machining products is generally associated with the surface roughness (Ra) which is one of the important aspects that could affect machining performances. This study seeks to find the minimum value of Ra for a modern machining process, Abrasive Water Jet (AWJ). This study proposed Cuckoo...

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Main Author:	Mohamad, Azizah
Format:	Thesis
Language:	English
Published:	2014
Subjects:	QA Mathematics
Online Access:	http://eprints.utm.my/id/eprint/48430/25/AzizahMohamadMFC2014.pdf
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id	my-utm-ep.48430
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spelling	my-utm-ep.484302017-09-12T04:33:56Z Enhancement of the machining surface roughness model with cuckoo algorithm 2014 Mohamad, Azizah QA Mathematics Quality of machining products is generally associated with the surface roughness (Ra) which is one of the important aspects that could affect machining performances. This study seeks to find the minimum value of Ra for a modern machining process, Abrasive Water Jet (AWJ). This study proposed Cuckoo algorithm to improve the surface roughness of the AWJ process because, since 2013, there has only been one study on the algorithm. Ra model in AWJ has five machining parameters comprising traverse speed (V), water jet pressure (P), standoff distance (h), abrasive grit size (D) and abrasive flow rate (m). These parameters in the Ra model have contributed to the best solution for machining performance by achieving the minimum values. In this study, to obtain better results, the parameters in the standard Ra model were enhanced in the modeling process where the number of parameters has been reduced. The enhanced parameters in the model are represented by “Q”. Computational techniques were used to evaluate the model whereas SPSS were used to validate the results. The result shows that minimum Ra value of the proposed model is 2.1709 µm. It was much lower than the results of three computational techniques which are Artificial Neural Network (ANN), Regression analysis and Support Vector Machine (SVM) by about 29.2 %, 23.8 % and 19.3% respectively. 2014 Thesis http://eprints.utm.my/id/eprint/48430/ http://eprints.utm.my/id/eprint/48430/25/AzizahMohamadMFC2014.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Mohamad, Azizah Enhancement of the machining surface roughness model with cuckoo algorithm
description	Quality of machining products is generally associated with the surface roughness (Ra) which is one of the important aspects that could affect machining performances. This study seeks to find the minimum value of Ra for a modern machining process, Abrasive Water Jet (AWJ). This study proposed Cuckoo algorithm to improve the surface roughness of the AWJ process because, since 2013, there has only been one study on the algorithm. Ra model in AWJ has five machining parameters comprising traverse speed (V), water jet pressure (P), standoff distance (h), abrasive grit size (D) and abrasive flow rate (m). These parameters in the Ra model have contributed to the best solution for machining performance by achieving the minimum values. In this study, to obtain better results, the parameters in the standard Ra model were enhanced in the modeling process where the number of parameters has been reduced. The enhanced parameters in the model are represented by “Q”. Computational techniques were used to evaluate the model whereas SPSS were used to validate the results. The result shows that minimum Ra value of the proposed model is 2.1709 µm. It was much lower than the results of three computational techniques which are Artificial Neural Network (ANN), Regression analysis and Support Vector Machine (SVM) by about 29.2 %, 23.8 % and 19.3% respectively.
format	Thesis
qualification_level	Master's degree
author	Mohamad, Azizah
author_facet	Mohamad, Azizah
author_sort	Mohamad, Azizah
title	Enhancement of the machining surface roughness model with cuckoo algorithm
title_short	Enhancement of the machining surface roughness model with cuckoo algorithm
title_full	Enhancement of the machining surface roughness model with cuckoo algorithm
title_fullStr	Enhancement of the machining surface roughness model with cuckoo algorithm
title_full_unstemmed	Enhancement of the machining surface roughness model with cuckoo algorithm
title_sort	enhancement of the machining surface roughness model with cuckoo algorithm
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2014
url	http://eprints.utm.my/id/eprint/48430/25/AzizahMohamadMFC2014.pdf
_version_	1747817388379734016

Enhancement of the machining surface roughness model with cuckoo algorithm

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