Optimizing production in machining of hardened steels using response surface methodology
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
DOI: | 10.4025/actascitechnol.v41i1.38091 |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/38091 |
Resumo: | This paper presents the modeling of tool life and surface roughness for machining AISI 52100 steel with a hardness of 50 HRC through Design of Experiments and Response Surface Methodology (RSM) with a view to enhance the quality and productivity. Knowing that the tool life and surface roughness are factors that influence the quality of the product, this study used the statistical tool of RSM in the search of factors that better determine optimal models. The models obtained prioritize the product quality and the cutting productivity. Results from Analysis of Variance demonstrated that the mathematical models elaborated allowed the prediction of surface roughness parameters’ values and tool life (T) with a precision of 95% confidence interval and a coefficient of determination above 94%. The wiper geometry of the tool led to the achievement of low average surface roughness (Ra) ranging from 0.2 to 0.4 µm with relatively high advances (0.2-0.4 mm rev-1) and maximum height of the profile surface roughness (Rt) in the range of 1.4 to 2.8 µm, without making use of the cutting fluid. |
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Acta scientiarum. Technology (Online) |
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Optimizing production in machining of hardened steels using response surface methodologydesign of experimentsresponse surface methodologyproduction optimizationEstatísticaPlanejamento de experimentosThis paper presents the modeling of tool life and surface roughness for machining AISI 52100 steel with a hardness of 50 HRC through Design of Experiments and Response Surface Methodology (RSM) with a view to enhance the quality and productivity. Knowing that the tool life and surface roughness are factors that influence the quality of the product, this study used the statistical tool of RSM in the search of factors that better determine optimal models. The models obtained prioritize the product quality and the cutting productivity. Results from Analysis of Variance demonstrated that the mathematical models elaborated allowed the prediction of surface roughness parameters’ values and tool life (T) with a precision of 95% confidence interval and a coefficient of determination above 94%. The wiper geometry of the tool led to the achievement of low average surface roughness (Ra) ranging from 0.2 to 0.4 µm with relatively high advances (0.2-0.4 mm rev-1) and maximum height of the profile surface roughness (Rt) in the range of 1.4 to 2.8 µm, without making use of the cutting fluid.Universidade Estadual De Maringá2019-05-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionOtimizaçãoapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/3809110.4025/actascitechnol.v41i1.38091Acta Scientiarum. Technology; Vol 41 (2019): Publicação Contínua; e38091Acta Scientiarum. Technology; v. 41 (2019): Publicação Contínua; e380911806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/38091/pdfCopyright (c) 2019 Acta Scientiarum. Technologyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessCampos, Paulo Henrique da SilvaPaes, Vinicius de CarvalhoGonçalves, Ernany Daniel de CarvalhoFerreira, João RobertoBalestrassi, Pedro PauloSilva, João Paulo Davim Tavares da2019-07-17T11:54:33Zoai:periodicos.uem.br/ojs:article/38091Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2019-07-17T11:54:33Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Optimizing production in machining of hardened steels using response surface methodology |
title |
Optimizing production in machining of hardened steels using response surface methodology |
spellingShingle |
Optimizing production in machining of hardened steels using response surface methodology Optimizing production in machining of hardened steels using response surface methodology Campos, Paulo Henrique da Silva design of experiments response surface methodology production optimization Estatística Planejamento de experimentos Campos, Paulo Henrique da Silva design of experiments response surface methodology production optimization Estatística Planejamento de experimentos |
title_short |
Optimizing production in machining of hardened steels using response surface methodology |
title_full |
Optimizing production in machining of hardened steels using response surface methodology |
title_fullStr |
Optimizing production in machining of hardened steels using response surface methodology Optimizing production in machining of hardened steels using response surface methodology |
title_full_unstemmed |
Optimizing production in machining of hardened steels using response surface methodology Optimizing production in machining of hardened steels using response surface methodology |
title_sort |
Optimizing production in machining of hardened steels using response surface methodology |
author |
Campos, Paulo Henrique da Silva |
author_facet |
Campos, Paulo Henrique da Silva Campos, Paulo Henrique da Silva Paes, Vinicius de Carvalho Gonçalves, Ernany Daniel de Carvalho Ferreira, João Roberto Balestrassi, Pedro Paulo Silva, João Paulo Davim Tavares da Paes, Vinicius de Carvalho Gonçalves, Ernany Daniel de Carvalho Ferreira, João Roberto Balestrassi, Pedro Paulo Silva, João Paulo Davim Tavares da |
author_role |
author |
author2 |
Paes, Vinicius de Carvalho Gonçalves, Ernany Daniel de Carvalho Ferreira, João Roberto Balestrassi, Pedro Paulo Silva, João Paulo Davim Tavares da |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Campos, Paulo Henrique da Silva Paes, Vinicius de Carvalho Gonçalves, Ernany Daniel de Carvalho Ferreira, João Roberto Balestrassi, Pedro Paulo Silva, João Paulo Davim Tavares da |
dc.subject.por.fl_str_mv |
design of experiments response surface methodology production optimization Estatística Planejamento de experimentos |
topic |
design of experiments response surface methodology production optimization Estatística Planejamento de experimentos |
description |
This paper presents the modeling of tool life and surface roughness for machining AISI 52100 steel with a hardness of 50 HRC through Design of Experiments and Response Surface Methodology (RSM) with a view to enhance the quality and productivity. Knowing that the tool life and surface roughness are factors that influence the quality of the product, this study used the statistical tool of RSM in the search of factors that better determine optimal models. The models obtained prioritize the product quality and the cutting productivity. Results from Analysis of Variance demonstrated that the mathematical models elaborated allowed the prediction of surface roughness parameters’ values and tool life (T) with a precision of 95% confidence interval and a coefficient of determination above 94%. The wiper geometry of the tool led to the achievement of low average surface roughness (Ra) ranging from 0.2 to 0.4 µm with relatively high advances (0.2-0.4 mm rev-1) and maximum height of the profile surface roughness (Rt) in the range of 1.4 to 2.8 µm, without making use of the cutting fluid. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-05-29 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Otimização |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/38091 10.4025/actascitechnol.v41i1.38091 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/38091 |
identifier_str_mv |
10.4025/actascitechnol.v41i1.38091 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/38091/pdf |
dc.rights.driver.fl_str_mv |
Copyright (c) 2019 Acta Scientiarum. Technology https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2019 Acta Scientiarum. Technology https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 41 (2019): Publicação Contínua; e38091 Acta Scientiarum. Technology; v. 41 (2019): Publicação Contínua; e38091 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1822182883400351744 |
dc.identifier.doi.none.fl_str_mv |
10.4025/actascitechnol.v41i1.38091 |