Prediction of tool deflection using image processing in ball-end milling

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dc.authoridÖzdemir, Burak/0000-0002-5870-0398
dc.authoridbahçe, erkan/0000-0001-5389-5571
dc.authorwosidÖzdemir, Burak/AAB-6654-2020
dc.authorwosidbahçe, erkan/AAQ-3631-2020
dc.contributor.authorOzdemir, Burak
dc.contributor.authorBahce, Erkan
dc.date.accessioned2024-08-04T20:53:11Z
dc.date.available2024-08-04T20:53:11Z
dc.date.issued2023
dc.departmentİnönü Üniversitesien_US
dc.description.abstractIn milling, some of the factors that contribute to the poor quality of products are the cutting forces. Depending on the machining parameters, the cutting forces may significantly affect the tool being used in the machining process. Tool deflection can be modeled as bending deformation. Tool deflection causes poor surface quality, geometrical and dimensional errors. For this reason, it must be addressed during milling and reduced by changing the machining parameters. In the determination of tool deflection, force-based analytical and finite element methods (FEM) and sensor measurement methods are widely used. These technologies have drawbacks such as not being able to obtain fast data, being expensive, demanding precise control, and requiring continual calibration. This study aims to determine the deflection of the tool by image processing dependent on the tool/material pair and machining parameters in the milling process. For this purpose, the AL7075 material with a free-form surface was machined on a CNC milling machine. A mathematical equation is proposed to estimate the tool deflection based on the image processing results. The method has shown that tool deviation can be detected more quickly and simply by image processing.en_US
dc.description.sponsorshipInonu University BAP [FDK-2020-2046]en_US
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by Inonu University BAP (Project number FDK-2020-2046).en_US
dc.identifier.doi10.1177/09544054221136398
dc.identifier.endpage1725en_US
dc.identifier.issn0954-4054
dc.identifier.issn2041-2975
dc.identifier.issue11en_US
dc.identifier.scopus2-s2.0-85142350634en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1716en_US
dc.identifier.urihttps://doi.org/10.1177/09544054221136398
dc.identifier.urihttps://hdl.handle.net/11616/101006
dc.identifier.volume237en_US
dc.identifier.wosWOS:000886758800001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSage Publications Ltden_US
dc.relation.ispartofProceedings of The Institution of Mechanical Engineers Part B-Journal of Engineering Manufactureen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMillingen_US
dc.subjectimage processingen_US
dc.subjecttool deflectionen_US
dc.titlePrediction of tool deflection using image processing in ball-end millingen_US
dc.typeArticleen_US

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