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dc.rights.licenseAttribution 4.0 International*
dc.contributor.authorAristimuño, Patxi Xabier
dc.contributor.authorBasagoiti, Rosa
dc.contributor.authorARRAZOLA, PEDRO JOSE
dc.contributor.authorLazkano Rayo, Xabier
dc.contributor.authorSela, Andrés
dc.date.accessioned2018-10-19T14:48:17Z
dc.date.available2018-10-19T14:48:17Z
dc.date.issued2018
dc.identifier.issn2212-8271eu_ES
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=148493eu_ES
dc.identifier.urihttps://hdl.handle.net/20.500.11984/1103
dc.description.abstractA material database for JETHETE-M152 was developed applying a novel methodology for improving the precision of cutting forces. This approach defines a variable specific edge force depending on the feed rate and cutting edge geometry. Applying this methodology, accurate predictions could be obtained when using complex shape inserts with different micro-geometries or with feed rates lower than the cutting edge radius. These predictions showed an improvement compared to those of the strategy of keeping constant the specific edge coefficient. Furthermore, an orthogonal to oblique transformation technique was applied to predict the cutting forces in face and side milling. The results showed good agreement with experimental results.eu_ES
dc.description.sponsorshipThe authors would like to thank to H2020 and to the Basque Government for the financial support given to the projects MC-SUITE (H2020 GA: 680478) and SMAPRO (KK-2017/00021).eu_ES
dc.language.isoengeu_ES
dc.publisherElsevier Ltd.eu_ES
dc.rights© 2018 The Authorseu_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectmodellingeu_ES
dc.subjectforceseu_ES
dc.subjectcutting edgeeu_ES
dc.subjectmillingeu_ES
dc.subjectJETHETE-M152eu_ES
dc.titleAn optimization methodology for material databases to improve cutting force predictions when milling martensitic stainless steel JETHETE-M152eu_ES
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2eu_ES
dcterms.sourceProcedia CIRPeu_ES
local.contributor.groupMecanizado de alto rendimientoeu_ES
local.description.peerreviewedtrueeu_ES
local.description.publicationfirstpage287eu_ES
local.description.publicationlastpage290eu_ES
local.identifier.doihttps://doi.org/10.1016/j.procir.2018.09.017eu_ES
local.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/680478/EU/ICT Powered Machining Software Suite/MC-SUITEeu_ES
local.relation.projectIDGobierno Vasco. Elkartek 2017. KK2017-00021. Máquinas y Procesos SMART a través de la Integración del Conocimiento y los Datos. SMAPROeu_ES
local.source.detailsVol. 77. Pp. 287-290, 2018eu_ES
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore
oaire.resourceTypehttp://purl.org/coar/resource_type/c_6501eu_ES
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85eu_ES


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Registro sencillo

Attribution 4.0 International
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