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An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method

Surface roughness is one of the most important requirements in machining process. In order to obtain needed surface roughness, the proper setting of cutting parameters is crucial before the process take place. Therefore, an accurate mathematical model to predict surface roughness is totally needed....

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Main Author: M. F. F., Ab Rashid
Format: Article
Language:English
English
Published: IACSIT Press 2015
Subjects:
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/6693/2/162-S103_Improved_Math_Model.pdf
http://umpir.ump.edu.my/id/eprint/6693/3/fkm-2014-fadzil-An_Improved_Mathematical.pdf
http://umpir.ump.edu.my/id/eprint/6693/
http://www.ijmmm.org/index.php?m=content&c=index&a=show&catid=34&id=201
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spelling my.ump.umpir.66932015-03-03T09:32:00Z http://umpir.ump.edu.my/id/eprint/6693/ An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method M. F. F., Ab Rashid TS Manufactures Surface roughness is one of the most important requirements in machining process. In order to obtain needed surface roughness, the proper setting of cutting parameters is crucial before the process take place. Therefore, an accurate mathematical model to predict surface roughness is totally needed. This research presents a hybrid method which combine conventional multiple regression analysis and genetic algorithm to improve the accuracy of mathematical model to predict surface roughness. In experiment, three independent variables: spindle speed, feed rate and depth of cut were manipulated in collecting data. Full factorials cut were performed using FANUC CNC Milling α-Τ14ιE. The results show that the proposed hybrid method capable to improve accuracy of model with 23% and 28% of reduction in error. IACSIT Press 2015-02-01 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6693/2/162-S103_Improved_Math_Model.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/6693/3/fkm-2014-fadzil-An_Improved_Mathematical.pdf M. F. F., Ab Rashid (2015) An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method. International Journal of Materials, Mechanics and Manufacturing, 3 (1). pp. 36-39. ISSN 1793-8198 http://www.ijmmm.org/index.php?m=content&c=index&a=show&catid=34&id=201 DOI: 10.7763/IJMMM.2015.V3.162
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic TS Manufactures
spellingShingle TS Manufactures
M. F. F., Ab Rashid
An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method
description Surface roughness is one of the most important requirements in machining process. In order to obtain needed surface roughness, the proper setting of cutting parameters is crucial before the process take place. Therefore, an accurate mathematical model to predict surface roughness is totally needed. This research presents a hybrid method which combine conventional multiple regression analysis and genetic algorithm to improve the accuracy of mathematical model to predict surface roughness. In experiment, three independent variables: spindle speed, feed rate and depth of cut were manipulated in collecting data. Full factorials cut were performed using FANUC CNC Milling α-Τ14ιE. The results show that the proposed hybrid method capable to improve accuracy of model with 23% and 28% of reduction in error.
format Article
author M. F. F., Ab Rashid
author_facet M. F. F., Ab Rashid
author_sort M. F. F., Ab Rashid
title An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method
title_short An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method
title_full An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method
title_fullStr An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method
title_full_unstemmed An Improved Mathematical Model to Predict Surface Roughness Using Hybrid Method
title_sort improved mathematical model to predict surface roughness using hybrid method
publisher IACSIT Press
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/6693/2/162-S103_Improved_Math_Model.pdf
http://umpir.ump.edu.my/id/eprint/6693/3/fkm-2014-fadzil-An_Improved_Mathematical.pdf
http://umpir.ump.edu.my/id/eprint/6693/
http://www.ijmmm.org/index.php?m=content&c=index&a=show&catid=34&id=201
_version_ 1643665443177627648
score 13.211869

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