Optimization of surface texture in milling using response surface methodology

This project deals with the effects of three parameters chosen on the surface texture of Aluminum 6061 by using milling. The main objectives of this project are to investigate the parameters for surface texture in milling, to obtain the optimum surface texture using Response Surface Methodology and...

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Main Author:	Syahrizad, Muhamad
Format:	Undergraduates Project Papers
Language:	English
Published:	2010
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/1499/ http://umpir.ump.edu.my/id/eprint/1499/ http://umpir.ump.edu.my/id/eprint/1499/1/Syahrizad_Muhamad_%28_CD_5047_%29.pdf

id	ump-1499
recordtype	eprints
spelling	ump-14992015-03-03T07:51:26Z http://umpir.ump.edu.my/id/eprint/1499/ Optimization of surface texture in milling using response surface methodology Syahrizad, Muhamad TA Engineering (General). Civil engineering (General) This project deals with the effects of three parameters chosen on the surface texture of Aluminum 6061 by using milling. The main objectives of this project are to investigate the parameters for surface texture in milling, to obtain the optimum surface texture using Response Surface Methodology and to recommend the best machine parameter that contributes to the optimum surface roughness value. The study of this project covers on the limitation of cutting speed range (100 to 180 mm), feed range of 0.1 to 0.2 min.mm and depth of cut range 1 to 2 tooth.mm. The 15 experiments (1 experiment consist of 1 pass that 90mm in length) are done by using manual coding of CNC Milling Machine, Perthometer for surface roughness testing and Metallurgical Microscope for surface texture testing. The result and data taken from these procedures were analyzed by using Response Surface Methodology (RSM) of Minitab Software. The model is validates through a comparison of the experimental values with their predicted counterparts. From the results, it indicates that from the RSM method, the first order gives 73.14% accuracy and the second order gives 81.43% in accuracy. The proved technique gives opportunities for better approach that could be applied to the calibration of other empirical models of machining. 2010-11 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1499/1/Syahrizad_Muhamad_%28_CD_5047_%29.pdf Syahrizad, Muhamad (2010) Optimization of surface texture in milling using response surface methodology. Faculty of Mechanical Engineering, Universiti Malaysia Pahang. http://iportal.ump.edu.my/lib/item?id=chamo:52370&theme=UMP2
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Syahrizad, Muhamad Optimization of surface texture in milling using response surface methodology
description	This project deals with the effects of three parameters chosen on the surface texture of Aluminum 6061 by using milling. The main objectives of this project are to investigate the parameters for surface texture in milling, to obtain the optimum surface texture using Response Surface Methodology and to recommend the best machine parameter that contributes to the optimum surface roughness value. The study of this project covers on the limitation of cutting speed range (100 to 180 mm), feed range of 0.1 to 0.2 min.mm and depth of cut range 1 to 2 tooth.mm. The 15 experiments (1 experiment consist of 1 pass that 90mm in length) are done by using manual coding of CNC Milling Machine, Perthometer for surface roughness testing and Metallurgical Microscope for surface texture testing. The result and data taken from these procedures were analyzed by using Response Surface Methodology (RSM) of Minitab Software. The model is validates through a comparison of the experimental values with their predicted counterparts. From the results, it indicates that from the RSM method, the first order gives 73.14% accuracy and the second order gives 81.43% in accuracy. The proved technique gives opportunities for better approach that could be applied to the calibration of other empirical models of machining.
format	Undergraduates Project Papers
author	Syahrizad, Muhamad
author_facet	Syahrizad, Muhamad
author_sort	Syahrizad, Muhamad
title	Optimization of surface texture in milling using response surface methodology
title_short	Optimization of surface texture in milling using response surface methodology
title_full	Optimization of surface texture in milling using response surface methodology
title_fullStr	Optimization of surface texture in milling using response surface methodology
title_full_unstemmed	Optimization of surface texture in milling using response surface methodology
title_sort	optimization of surface texture in milling using response surface methodology
publishDate	2010
url	http://umpir.ump.edu.my/id/eprint/1499/ http://umpir.ump.edu.my/id/eprint/1499/ http://umpir.ump.edu.my/id/eprint/1499/1/Syahrizad_Muhamad_%28_CD_5047_%29.pdf
first_indexed	2023-09-18T21:54:41Z
last_indexed	2023-09-18T21:54:41Z
_version_	1777413999854354432

Optimization of surface texture in milling using response surface methodology

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