Development of New Genetic Algorithm Software for Blow Mould Process

This paper is concerned on the optimization of the surface roughness when milling mould aluminium alloys (AA6061-T6) with carbide coated inserts with newly develop Genetic Algorithm (GA) software. Optimization of the milling is very useful to reduce cost and time for machining mould. The appro...

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Main Authors: K., Kadirgama, M. M., Noor, R., Daud, M. R. M., Rejab
Format: Conference or Workshop Item
Language:English
Published: 2008
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/1274/
http://umpir.ump.edu.my/id/eprint/1274/1/Development_of_New_Genetic_Algorithm_Software_for_Blow_Mould_Process.pdf
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author K., Kadirgama
M. M., Noor
R., Daud
M. R. M., Rejab
author_facet K., Kadirgama
M. M., Noor
R., Daud
M. R. M., Rejab
author_sort K., Kadirgama
building UMP Institutional Repository
collection Online Access
description This paper is concerned on the optimization of the surface roughness when milling mould aluminium alloys (AA6061-T6) with carbide coated inserts with newly develop Genetic Algorithm (GA) software. Optimization of the milling is very useful to reduce cost and time for machining mould. The approach is based on newly development of Genetic Algorithm software. In this work, the objectives were to optimized parameters with newly develop software and compare with statistical software. The optimized value has been used to develop a blow mould. Results from the newly develop GA software is closer with the statistical software. This software directly reduces in term of machining cost.
first_indexed 2025-11-15T01:11:57Z
format Conference or Workshop Item
id ump-1274
institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T01:11:57Z
publishDate 2008
recordtype eprints
repository_type Digital Repository
spelling ump-12742018-01-31T02:02:20Z http://umpir.ump.edu.my/id/eprint/1274/ Development of New Genetic Algorithm Software for Blow Mould Process K., Kadirgama M. M., Noor R., Daud M. R. M., Rejab TJ Mechanical engineering and machinery This paper is concerned on the optimization of the surface roughness when milling mould aluminium alloys (AA6061-T6) with carbide coated inserts with newly develop Genetic Algorithm (GA) software. Optimization of the milling is very useful to reduce cost and time for machining mould. The approach is based on newly development of Genetic Algorithm software. In this work, the objectives were to optimized parameters with newly develop software and compare with statistical software. The optimized value has been used to develop a blow mould. Results from the newly develop GA software is closer with the statistical software. This software directly reduces in term of machining cost. 2008 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1274/1/Development_of_New_Genetic_Algorithm_Software_for_Blow_Mould_Process.pdf K., Kadirgama and M. M., Noor and R., Daud and M. R. M., Rejab (2008) Development of New Genetic Algorithm Software for Blow Mould Process. In: Malaysian Science and Technology Congress, MSTC08 , 16-17 Dec 2008 , KLCC, Malaysia. . (Unpublished) (Unpublished)
spellingShingle TJ Mechanical engineering and machinery
K., Kadirgama
M. M., Noor
R., Daud
M. R. M., Rejab
Development of New Genetic Algorithm Software for Blow Mould Process
title Development of New Genetic Algorithm Software for Blow Mould Process
title_full Development of New Genetic Algorithm Software for Blow Mould Process
title_fullStr Development of New Genetic Algorithm Software for Blow Mould Process
title_full_unstemmed Development of New Genetic Algorithm Software for Blow Mould Process
title_short Development of New Genetic Algorithm Software for Blow Mould Process
title_sort development of new genetic algorithm software for blow mould process
topic TJ Mechanical engineering and machinery
url http://umpir.ump.edu.my/id/eprint/1274/
http://umpir.ump.edu.my/id/eprint/1274/1/Development_of_New_Genetic_Algorithm_Software_for_Blow_Mould_Process.pdf