Surface Roughness Analysis In End Milling With Response Ant Colony Optimization

The increase of consumer needs for quality metal cutting related products (more precise tolerances and better product surface roughness) has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Within these metal cutting processes, the end-milling pro...

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Main Authors:	K., Kadirgama, M. M., Noor, M. M., Rahman, M. S. M., Sani
Format:	Conference or Workshop Item
Language:	English
Published:	2009
Subjects:	TJ Mechanical engineering and machinery
Online Access:	http://umpir.ump.edu.my/id/eprint/1448/ http://umpir.ump.edu.my/id/eprint/1448/1/2009_P_NAE09_K.Kadirgama_M.M.Noor-conference-.pdf

id	ump-1448
recordtype	eprints
spelling	ump-14482018-01-22T07:24:27Z http://umpir.ump.edu.my/id/eprint/1448/ Surface Roughness Analysis In End Milling With Response Ant Colony Optimization K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani TJ Mechanical engineering and machinery The increase of consumer needs for quality metal cutting related products (more precise tolerances and better product surface roughness) has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Within these metal cutting processes, the end-milling process is one of the most fundamental metal removal operations used in the manufacturing industry. Surface roughness also affects several functional attributes of part such as contact causing surface friction, wearing, light reflection, heat transmission ability of distributing holding and lubricant, coating, or resisting fatigue. Therefore, the desired finish surface is usually specified and the appropriate processes are select to reach the required quality.This paper presents the optimization of the surface roughness when milling Mould Aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant colony Optimization (ACO). In this work, the objectives were to find the optimized parameters and find out the most dominant variables (cutting speed, federate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factors effecting surface roughness. The optimised minimum and maximum values that predicted by RACO were 0.36 μm and 1.37 μm. 2009 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1448/1/2009_P_NAE09_K.Kadirgama_M.M.Noor-conference-.pdf K., Kadirgama and M. M., Noor and M. M., Rahman and M. S. M., Sani (2009) Surface Roughness Analysis In End Milling With Response Ant Colony Optimization. In: 6th International Conference on Numerical Analysis in Engineering (NAE2009), 15 -16 May 2009 , Lombok Island, Mataram City, West Nusa Tenggara Province, Indonesia. . (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani Surface Roughness Analysis In End Milling With Response Ant Colony Optimization
description	The increase of consumer needs for quality metal cutting related products (more precise tolerances and better product surface roughness) has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Within these metal cutting processes, the end-milling process is one of the most fundamental metal removal operations used in the manufacturing industry. Surface roughness also affects several functional attributes of part such as contact causing surface friction, wearing, light reflection, heat transmission ability of distributing holding and lubricant, coating, or resisting fatigue. Therefore, the desired finish surface is usually specified and the appropriate processes are select to reach the required quality.This paper presents the optimization of the surface roughness when milling Mould Aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant colony Optimization (ACO). In this work, the objectives were to find the optimized parameters and find out the most dominant variables (cutting speed, federate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factors effecting surface roughness. The optimised minimum and maximum values that predicted by RACO were 0.36 μm and 1.37 μm.
format	Conference or Workshop Item
author	K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani
author_facet	K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani
author_sort	K., Kadirgama
title	Surface Roughness Analysis In End Milling With Response Ant Colony Optimization
title_short	Surface Roughness Analysis In End Milling With Response Ant Colony Optimization
title_full	Surface Roughness Analysis In End Milling With Response Ant Colony Optimization
title_fullStr	Surface Roughness Analysis In End Milling With Response Ant Colony Optimization
title_full_unstemmed	Surface Roughness Analysis In End Milling With Response Ant Colony Optimization
title_sort	surface roughness analysis in end milling with response ant colony optimization
publishDate	2009
url	http://umpir.ump.edu.my/id/eprint/1448/ http://umpir.ump.edu.my/id/eprint/1448/1/2009_P_NAE09_K.Kadirgama_M.M.Noor-conference-.pdf
first_indexed	2023-09-18T21:54:35Z
last_indexed	2023-09-18T21:54:35Z
_version_	1777413994306338816

Surface Roughness Analysis In End Milling With Response Ant Colony Optimization

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