Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry

Detalhes bibliográficos
Autor(a) principal: Vookoti, Uma Sai Vara Prasad
Data de Publicação: 2022
Outros Autores: K., Venkata Rao, P., Satish Kumar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Independent Journal of Management & Production
Texto Completo: http://www.ijmp.jor.br/index.php/ijmp/article/view/1617
Resumo: Helical milling is one of the high-performance and high-quality hole manufacturing activities with strong prospects for the automotive and aerospace industries. Literature suggests chip geometry plays a significant role in optimizing machining operations. In the present study, a mechanistic approach is used to estimate the chip geometry, cutting force and power/energy consumption concerning the tool rotation angle. Experiments are conducted at different levels of spindle rotational speed, cutter orbital speed and axial depth of cuts using 8 and 10 mm diameter mill cutters. Experimental results for cutting speed in X, Y and Z directions are measured. A hybrid approach, which combines the Taguchi method and Graph theory and matrix approach (GTMA) technique is used and optimized process parameters. The highest aggregate utility process parameters are met by 2000 rpm spindle speed, 50 rpm orbital speed and 0.2 mm axial cutting depth during helical milling of AISI D2 steel. FEM simulation is used for predicting the chip thickness, cutting forces and power consumption and also validated the optimization.
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spelling Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometryHelical millingCutting forcesEnergy consumptionGTMAChip geometryHelical milling is one of the high-performance and high-quality hole manufacturing activities with strong prospects for the automotive and aerospace industries. Literature suggests chip geometry plays a significant role in optimizing machining operations. In the present study, a mechanistic approach is used to estimate the chip geometry, cutting force and power/energy consumption concerning the tool rotation angle. Experiments are conducted at different levels of spindle rotational speed, cutter orbital speed and axial depth of cuts using 8 and 10 mm diameter mill cutters. Experimental results for cutting speed in X, Y and Z directions are measured. A hybrid approach, which combines the Taguchi method and Graph theory and matrix approach (GTMA) technique is used and optimized process parameters. The highest aggregate utility process parameters are met by 2000 rpm spindle speed, 50 rpm orbital speed and 0.2 mm axial cutting depth during helical milling of AISI D2 steel. FEM simulation is used for predicting the chip thickness, cutting forces and power consumption and also validated the optimization.Independent2022-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://www.ijmp.jor.br/index.php/ijmp/article/view/161710.14807/ijmp.v13i2.1617Independent Journal of Management & Production; Vol. 13 No. 2 (2022): Independent Journal of Management & Production; 750-7702236-269X2236-269Xreponame:Independent Journal of Management & Productioninstname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)instacron:IJM&Penghttp://www.ijmp.jor.br/index.php/ijmp/article/view/1617/2139Copyright (c) 2021 UMA SAI VARA PRASAD VOOKOTI, Satish Kumar Phttp://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessVookoti, Uma Sai Vara PrasadK., Venkata RaoP., Satish Kumar2022-05-01T13:22:54Zoai:www.ijmp.jor.br:article/1617Revistahttp://www.ijmp.jor.br/PUBhttp://www.ijmp.jor.br/index.php/ijmp/oaiijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br||2236-269X2236-269Xopendoar:2022-05-01T13:22:54Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)false
dc.title.none.fl_str_mv Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
title Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
spellingShingle Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
Vookoti, Uma Sai Vara Prasad
Helical milling
Cutting forces
Energy consumption
GTMA
Chip geometry
title_short Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
title_full Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
title_fullStr Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
title_full_unstemmed Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
title_sort Optimization of machining characteristics during helical milling of AISI D2 steel considering chip geometry
author Vookoti, Uma Sai Vara Prasad
author_facet Vookoti, Uma Sai Vara Prasad
K., Venkata Rao
P., Satish Kumar
author_role author
author2 K., Venkata Rao
P., Satish Kumar
author2_role author
author
dc.contributor.author.fl_str_mv Vookoti, Uma Sai Vara Prasad
K., Venkata Rao
P., Satish Kumar
dc.subject.por.fl_str_mv Helical milling
Cutting forces
Energy consumption
GTMA
Chip geometry
topic Helical milling
Cutting forces
Energy consumption
GTMA
Chip geometry
description Helical milling is one of the high-performance and high-quality hole manufacturing activities with strong prospects for the automotive and aerospace industries. Literature suggests chip geometry plays a significant role in optimizing machining operations. In the present study, a mechanistic approach is used to estimate the chip geometry, cutting force and power/energy consumption concerning the tool rotation angle. Experiments are conducted at different levels of spindle rotational speed, cutter orbital speed and axial depth of cuts using 8 and 10 mm diameter mill cutters. Experimental results for cutting speed in X, Y and Z directions are measured. A hybrid approach, which combines the Taguchi method and Graph theory and matrix approach (GTMA) technique is used and optimized process parameters. The highest aggregate utility process parameters are met by 2000 rpm spindle speed, 50 rpm orbital speed and 0.2 mm axial cutting depth during helical milling of AISI D2 steel. FEM simulation is used for predicting the chip thickness, cutting forces and power consumption and also validated the optimization.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.ijmp.jor.br/index.php/ijmp/article/view/1617
10.14807/ijmp.v13i2.1617
url http://www.ijmp.jor.br/index.php/ijmp/article/view/1617
identifier_str_mv 10.14807/ijmp.v13i2.1617
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.ijmp.jor.br/index.php/ijmp/article/view/1617/2139
dc.rights.driver.fl_str_mv Copyright (c) 2021 UMA SAI VARA PRASAD VOOKOTI, Satish Kumar P
http://creativecommons.org/licenses/by-nc-sa/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 UMA SAI VARA PRASAD VOOKOTI, Satish Kumar P
http://creativecommons.org/licenses/by-nc-sa/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Independent
publisher.none.fl_str_mv Independent
dc.source.none.fl_str_mv Independent Journal of Management & Production; Vol. 13 No. 2 (2022): Independent Journal of Management & Production; 750-770
2236-269X
2236-269X
reponame:Independent Journal of Management & Production
instname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
instacron:IJM&P
instname_str Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
instacron_str IJM&P
institution IJM&P
reponame_str Independent Journal of Management & Production
collection Independent Journal of Management & Production
repository.name.fl_str_mv Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
repository.mail.fl_str_mv ijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br||
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