A novel hybrid model for prediction of distortions in milling

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dc.contributor.authorid0000-0003-4564-7337
dc.contributor.authorid0000-0002-8316-9623
dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Mechanical Engineering
dc.contributor.kuauthorAkhtar, Waseem
dc.contributor.kuauthorLazoğlu, İsmail
dc.contributor.kuprofilePhD Student
dc.contributor.kuprofileFaculty Member
dc.contributor.researchcenterMARC (Manufacturing and Automation Research Center)
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid179391
dc.date.accessioned2025-01-19T10:27:52Z
dc.date.issued2023
dc.description.abstractDistortion of machined monolithic thin-walled parts is a well-known issue and a perpetual concern in the aerospace industry. In this article, a novel analytical-FEM hybrid model for fast prediction of distortion of thin-walled parts is proposed. Moving cutting loads due to milling are calibrated and applied directly to the surface of the meshed model. The effects of measured initial stresses in the workpiece as well as cutting forces and heat flux are effectively modeled. Validation tests carried out on the aerospace alloy Al7050-T7451 showed the promise of the model in predicting the distortion of the part.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.issue1
dc.description.publisherscopeInternational
dc.description.sponsorsThe authors would like to thank Siemens for supporting this research via Ko , cUniversity Siemens IoT Edge Research Laboratory and thank Ar , c elik A. , S. for the WEDM support.
dc.description.volume72
dc.identifier.doi10.1016/j.cirp.2023.04.052
dc.identifier.eissn1726-0604
dc.identifier.issn0007-8506
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-85152357128
dc.identifier.urihttps://doi.org/10.1016/j.cirp.2023.04.052
dc.identifier.urihttps://hdl.handle.net/20.500.14288/25626
dc.identifier.wos1054413700001
dc.keywordsDeformation
dc.keywordsPredictive model
dc.keywordsMilling
dc.languageen
dc.publisherElsevier
dc.relation.grantnoSiemens
dc.sourceCirp Annals-Manufacturing Technology
dc.subjectEngineering, industrial
dc.subjectEngineering, Manufacturing
dc.titleA novel hybrid model for prediction of distortions in milling
dc.typeJournal Article

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