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dc.contributor.authorEtxebeste , Mikel
dc.contributor.authorOrtiz-de-Zarate, Gorka
dc.contributor.authorARRIETA, Iñaki Mirena
dc.contributor.authorARRAZOLA, PEDRO JOSE
dc.date.accessioned2025-03-12T16:46:35Z
dc.date.available2025-03-12T16:46:35Z
dc.date.issued2025
dc.identifier.issn1526-6125en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=180105en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/6917
dc.description.abstractLarge cutting tools are widely used in sectors such as automotive, where complex shape aluminium components are machined at high cutting speeds, in a single clamping and in short cycle times with elevated Material Removal Rate (MRR). However, their relatively low stiffness and natural frequencies make chatter the primary productivity limitation. Developing optimised tools to overcome these limitations is often cost-prohibitive with current design methods. This paper presents a virtual design methodology for optimising large milling tools to mitigate chatter through topology optimisation and Finite Element Modal Analysis (FEMA). Topology optimisation enhanced tool dynamics, enabling chatter reduction under higher productivity conditions. An improved FEMA model was developed to accurately predict the modal parameters of the cutting tools, featuring a high-fidelity representation of the tool-holder clamping to the spindle. The predicted modal parameters enable cost-effective chatter prediction for tool design validations, minimising development and experimental costs. To validate the methodology, a prototype of the optimised tool was manufactured and tested through experimental modal analysis and machining tests, demonstrating significant productivity improvement in MRR compared to the initial design.en
dc.language.isoengen
dc.publisherElsevieren
dc.rights© 2025 The Authorsen
dc.titleA virtual design methodology to improve the dynamics and productivity of large milling toolsen
dcterms.accessRightshttp://purl.org/coar/access_right/c_f1cfen
dcterms.sourceJournal of Manufacturing Processesen
local.contributor.groupMecanizado de alto rendimientoes
local.description.peerreviewedfalseen
local.identifier.doihttps://doi.org/10.1016/j.jmapro.2025.01.024en
local.embargo.enddate2027-01-31
local.source.detailsVol. 134. Pp. 1096-1113. January, 2025en
oaire.format.mimetypeapplication/pdfen
oaire.file$DSPACE\assetstoreen
oaire.resourceTypehttp://purl.org/coar/resource_type/c_6501en
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen
oaire.funderNameGobierno Vascoen
oaire.funderNameGobierno Vascoen
oaire.funderNameGobierno de Españaen
oaire.funderIdentifierhttps://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086en
oaire.funderIdentifierhttps://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086en
oaire.funderIdentifierhttps://ror.org/038jjxj40 / http://data.crossref.org/fundingdata/funder/10.13039/501100010198
oaire.fundingStreamElkartek 2024en
oaire.fundingStreamPrograma de apoyo a la I+D Empresarial Hazitek 2022en
oaire.fundingStreamProyectos de Generación de Conocimiento y a actuaciones para la formación de personal investigador predoctoralen
oaire.awardNumberKK-2024-00005en
oaire.awardNumberZL-2022-00741en
oaire.awardNumberPID2022-139655OB-I00en
oaire.awardTitleNueva generación de procesos para la (re)fabricación sostenible (ORLEGI)en
oaire.awardTitleEVMACHen
oaire.awardTitleDiseño a medida de la integridad superficial de los componentes mecanizados para mejorar su durabilidad en aplicaciones de salud y Aeronáuticas (TAILORSURF)en
oaire.awardURISin informaciónen
oaire.awardURISin informaciónen
oaire.awardURISin informaciónen


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