Optimizing surface finish in WEDM using the taguchi parameter design method
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782010000200002 |
Resumo: | Wire electrical discharge machining (WEDM) is extensively used in machining of materials when precision is of major factor. Selection of optimum machining parameter combinations for obtaining higher accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complex stochastic process mechanisms. In the present work, WEDM of titanium alloy (Ti6Al4V) is experimentally studied. The behavior of eight control parameters such as Ignition pulse current (A), Short pulse duration(B), Time between two pulses(C), Servo speed(D), Servo reference voltage(E), Injection pressure(F), Wire speed(G) and Wire tension(H) on surface finish was studied using Taguchi parameter design. A mathematical model is developed by means of linear regression analysis to establish relationship between control parameters and surface finish as process response. An attempt is made to optimize the surface roughness prediction model using Genetic Algorithm (GA). Optimum values of control parameters at level A1, B1, C1, D3, E1, F3, G2, H3 for the selected range and workpiece material are obtained. |
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Optimizing surface finish in WEDM using the taguchi parameter design methodWEDMtitanium alloysurface roughnessmodelinggenetic algorithmWire electrical discharge machining (WEDM) is extensively used in machining of materials when precision is of major factor. Selection of optimum machining parameter combinations for obtaining higher accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complex stochastic process mechanisms. In the present work, WEDM of titanium alloy (Ti6Al4V) is experimentally studied. The behavior of eight control parameters such as Ignition pulse current (A), Short pulse duration(B), Time between two pulses(C), Servo speed(D), Servo reference voltage(E), Injection pressure(F), Wire speed(G) and Wire tension(H) on surface finish was studied using Taguchi parameter design. A mathematical model is developed by means of linear regression analysis to establish relationship between control parameters and surface finish as process response. An attempt is made to optimize the surface roughness prediction model using Genetic Algorithm (GA). Optimum values of control parameters at level A1, B1, C1, D3, E1, F3, G2, H3 for the selected range and workpiece material are obtained.Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM2010-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782010000200002Journal of the Brazilian Society of Mechanical Sciences and Engineering v.32 n.2 2010reponame:Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)instname:Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)instacron:ABCM10.1590/S1678-58782010000200002info:eu-repo/semantics/openAccessPasam,Vamsi KrishnaBattula,Surendra BabuMadar Valli,P.Swapna,M.eng2010-08-31T00:00:00Zoai:scielo:S1678-58782010000200002Revistahttps://www.scielo.br/j/jbsmse/https://old.scielo.br/oai/scielo-oai.php||abcm@abcm.org.br1806-36911678-5878opendoar:2010-08-31T00:00Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) - Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)false |
dc.title.none.fl_str_mv |
Optimizing surface finish in WEDM using the taguchi parameter design method |
title |
Optimizing surface finish in WEDM using the taguchi parameter design method |
spellingShingle |
Optimizing surface finish in WEDM using the taguchi parameter design method Pasam,Vamsi Krishna WEDM titanium alloy surface roughness modeling genetic algorithm |
title_short |
Optimizing surface finish in WEDM using the taguchi parameter design method |
title_full |
Optimizing surface finish in WEDM using the taguchi parameter design method |
title_fullStr |
Optimizing surface finish in WEDM using the taguchi parameter design method |
title_full_unstemmed |
Optimizing surface finish in WEDM using the taguchi parameter design method |
title_sort |
Optimizing surface finish in WEDM using the taguchi parameter design method |
author |
Pasam,Vamsi Krishna |
author_facet |
Pasam,Vamsi Krishna Battula,Surendra Babu Madar Valli,P. Swapna,M. |
author_role |
author |
author2 |
Battula,Surendra Babu Madar Valli,P. Swapna,M. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Pasam,Vamsi Krishna Battula,Surendra Babu Madar Valli,P. Swapna,M. |
dc.subject.por.fl_str_mv |
WEDM titanium alloy surface roughness modeling genetic algorithm |
topic |
WEDM titanium alloy surface roughness modeling genetic algorithm |
description |
Wire electrical discharge machining (WEDM) is extensively used in machining of materials when precision is of major factor. Selection of optimum machining parameter combinations for obtaining higher accuracy is a challenging task in WEDM due to the presence of a large number of process variables and complex stochastic process mechanisms. In the present work, WEDM of titanium alloy (Ti6Al4V) is experimentally studied. The behavior of eight control parameters such as Ignition pulse current (A), Short pulse duration(B), Time between two pulses(C), Servo speed(D), Servo reference voltage(E), Injection pressure(F), Wire speed(G) and Wire tension(H) on surface finish was studied using Taguchi parameter design. A mathematical model is developed by means of linear regression analysis to establish relationship between control parameters and surface finish as process response. An attempt is made to optimize the surface roughness prediction model using Genetic Algorithm (GA). Optimum values of control parameters at level A1, B1, C1, D3, E1, F3, G2, H3 for the selected range and workpiece material are obtained. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782010000200002 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782010000200002 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1678-58782010000200002 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM |
dc.source.none.fl_str_mv |
Journal of the Brazilian Society of Mechanical Sciences and Engineering v.32 n.2 2010 reponame:Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) instname:Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM) instacron:ABCM |
instname_str |
Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM) |
instacron_str |
ABCM |
institution |
ABCM |
reponame_str |
Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) |
collection |
Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) |
repository.name.fl_str_mv |
Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online) - Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM) |
repository.mail.fl_str_mv |
||abcm@abcm.org.br |
_version_ |
1754734681483378688 |