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Response Ant Colony Optimization of End Milling Surface Roughness

Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper...

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Detalles Bibliográficos
Autores principales: Kadirgama, K., Noor, M. M., Abd Alla, Ahmed N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264467/
https://www.ncbi.nlm.nih.gov/pubmed/22294914
http://dx.doi.org/10.3390/s100302054
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author Kadirgama, K.
Noor, M. M.
Abd Alla, Ahmed N.
author_facet Kadirgama, K.
Noor, M. M.
Abd Alla, Ahmed N.
author_sort Kadirgama, K.
collection PubMed
description Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using 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). The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factor affecting surface roughness.
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spelling pubmed-32644672012-01-31 Response Ant Colony Optimization of End Milling Surface Roughness Kadirgama, K. Noor, M. M. Abd Alla, Ahmed N. Sensors (Basel) Article Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using 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). The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factor affecting surface roughness. Molecular Diversity Preservation International (MDPI) 2010-03-15 /pmc/articles/PMC3264467/ /pubmed/22294914 http://dx.doi.org/10.3390/s100302054 Text en © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Kadirgama, K.
Noor, M. M.
Abd Alla, Ahmed N.
Response Ant Colony Optimization of End Milling Surface Roughness
title Response Ant Colony Optimization of End Milling Surface Roughness
title_full Response Ant Colony Optimization of End Milling Surface Roughness
title_fullStr Response Ant Colony Optimization of End Milling Surface Roughness
title_full_unstemmed Response Ant Colony Optimization of End Milling Surface Roughness
title_short Response Ant Colony Optimization of End Milling Surface Roughness
title_sort response ant colony optimization of end milling surface roughness
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3264467/
https://www.ncbi.nlm.nih.gov/pubmed/22294914
http://dx.doi.org/10.3390/s100302054
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