ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness

Abstract Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned a...

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Autor principal:	Shakir M Mousa
Formato:	article
Lenguaje:	EN
Publicado:	Al-Khwarizmi College of Engineering – University of Baghdad 2017
Materias:	MAF process, MINITAB software, parameters, Signal-to-Noise ratio, surface roughness, Taguchi orthogonal array. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/5cda91bd84b14485a7d022ca80a2abac
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spelling	oai:doaj.org-article:5cda91bd84b14485a7d022ca80a2abac2021-12-02T07:16:40Zptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness10.22153/kej.2017.12.0011818-11712312-0789https://doaj.org/article/5cda91bd84b14485a7d022ca80a2abac2017-12-01T00:00:00Zhttp://alkej.uobaghdad.edu.iq/index.php/alkej/article/view/345https://doaj.org/toc/1818-1171https://doaj.org/toc/2312-0789 Abstract Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment (DOE) and response surface methodology (RSM).These six input parameters in this research were optimized for all input parameters to improve the surface layer for work piece by using signal-to-noise ratio technique. The obtained results showed that all six input parameters have an influence on the change in surface roughness(∆Ra). In addition, the results showed that the surface roughness of the work piece decreased from 1.130 to 0.370µm that means high level of improvement in the change of surface roughness (0.760)µm. Keywords: MAF process, MINITAB software, parameters, Signal-to-Noise ratio, surface roughness, Taguchi orthogonal array. Shakir M MousaAl-Khwarizmi College of Engineering – University of BaghdadarticleMAF process, MINITAB software, parameters, Signal-to-Noise ratio, surface roughness, Taguchi orthogonal array.Chemical engineeringTP155-156Engineering (General). Civil engineering (General)TA1-2040ENAl-Khawarizmi Engineering Journal, Vol 13, Iss 2 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	MAF process, MINITAB software, parameters, Signal-to-Noise ratio, surface roughness, Taguchi orthogonal array. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	MAF process, MINITAB software, parameters, Signal-to-Noise ratio, surface roughness, Taguchi orthogonal array. Chemical engineering TP155-156 Engineering (General). Civil engineering (General) TA1-2040 Shakir M Mousa ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
description	Abstract Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment (DOE) and response surface methodology (RSM).These six input parameters in this research were optimized for all input parameters to improve the surface layer for work piece by using signal-to-noise ratio technique. The obtained results showed that all six input parameters have an influence on the change in surface roughness(∆Ra). In addition, the results showed that the surface roughness of the work piece decreased from 1.130 to 0.370µm that means high level of improvement in the change of surface roughness (0.760)µm. Keywords: MAF process, MINITAB software, parameters, Signal-to-Noise ratio, surface roughness, Taguchi orthogonal array.
format	article
author	Shakir M Mousa
author_facet	Shakir M Mousa
author_sort	Shakir M Mousa
title	ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
title_short	ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
title_full	ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
title_fullStr	ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
title_full_unstemmed	ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
title_sort	ptimization the parameters of magnetic abrasive process using taguchi method to improve the surface roughness
publisher	Al-Khwarizmi College of Engineering – University of Baghdad
publishDate	2017
url	https://doaj.org/article/5cda91bd84b14485a7d022ca80a2abac
work_keys_str_mv	AT shakirmmousa ptimizationtheparametersofmagneticabrasiveprocessusingtaguchimethodtoimprovethesurfaceroughness
_version_	1718399516442361856

ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness

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