Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature

Detalhes bibliográficos
Autor(a) principal: Oraby,S. E.
Data de Publicação: 2008
Outros Autores: Alaskari,A. M.
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=S1678-58782008000300007
Resumo: One of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge's random deformation.
id ABCM-2_fc11afdbbc803412e69be061a80255d6
oai_identifier_str oai:scielo:S1678-58782008000300007
network_acronym_str ABCM-2
network_name_str Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)
repository_id_str
spelling Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signaturedynamic force signalssurface roughness/finishtool wear and deformationtool wear modes/nose, flankOne of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge's random deformation.Associação Brasileira de Engenharia e Ciências Mecânicas - ABCM2008-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782008000300007Journal of the Brazilian Society of Mechanical Sciences and Engineering v.30 n.3 2008reponame:Journal of the Brazilian Society of Mechanical Sciences and Engineering (Online)instname:Associação Brasileira de Engenharia e Ciências Mecânicas (ABCM)instacron:ABCM10.1590/S1678-58782008000300007info:eu-repo/semantics/openAccessOraby,S. E.Alaskari,A. M.eng2008-10-09T00:00:00Zoai:scielo:S1678-58782008000300007Revistahttps://www.scielo.br/j/jbsmse/https://old.scielo.br/oai/scielo-oai.php||abcm@abcm.org.br1806-36911678-5878opendoar:2008-10-09T00:00Journal 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 Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
title Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
spellingShingle Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
Oraby,S. E.
dynamic force signals
surface roughness/finish
tool wear and deformation
tool wear modes/nose, flank
title_short Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
title_full Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
title_fullStr Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
title_full_unstemmed Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
title_sort Surface topography assessment techniques based on an in-process monitoring approach of tool wear and cutting force signature
author Oraby,S. E.
author_facet Oraby,S. E.
Alaskari,A. M.
author_role author
author2 Alaskari,A. M.
author2_role author
dc.contributor.author.fl_str_mv Oraby,S. E.
Alaskari,A. M.
dc.subject.por.fl_str_mv dynamic force signals
surface roughness/finish
tool wear and deformation
tool wear modes/nose, flank
topic dynamic force signals
surface roughness/finish
tool wear and deformation
tool wear modes/nose, flank
description One of the most influential sources in machining affecting surface roughness is the instantaneous state of tool edge. The main objective of the current work is to relate the in-process immeasurable cutting edge deformation and surface roughness to a more reliable easy-to-measure force signals using a robust non-linear time-dependent modeling regression techniques. Correlation between wear propagation and roughness variation is developed throughout the different edge lifetimes. The surface roughness is further evaluated in the light of the variation in both the static and the dynamic force signals. Consistent correlation is found between surface roughness variation and tool wear progress within its initial and constant regions. At the first few seconds of cutting, expected and well known trend of the effect of the cutting parameters is observed. Surface roughness is positively influenced by the level of the feed rate and negatively by the cutting speed. As cutting continues, roughness is affected, to different extents, by the rather localized wear modes either on the tool nose or on its flank areas. Moreover, it seems that roughness varies as wear attitude transfers from one mode to another and, in general, it is shown that it is improved as wear increases but with possible corresponding workpart dimensional inaccuracy. The dynamic force signals are found reasonably sensitive to simulate either the progressive or the random modes of tool edge deformation. While the frictional force components, feeding and radial, are found informative regarding progressive wear modes, the vertical (power) components is found more representative carrier to system instability resulting from the edge's random deformation.
publishDate 2008
dc.date.none.fl_str_mv 2008-09-01
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=S1678-58782008000300007
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-58782008000300007
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1678-58782008000300007
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.30 n.3 2008
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_ 1754734681371181056