Investigation of machinability indicators during sustainable milling of 17-4PH stainless steel under dry and MQL environments

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dc.authoridGUNAY, MUSTAFA/0000-0002-1281-1359
dc.authoridYurtkuran, Hakan/0000-0003-2375-7316
dc.contributor.authorYurtkuran, Hakan
dc.contributor.authorBoy, Mehmet
dc.contributor.authorGunay, Mustafa
dc.date.accessioned2024-09-29T16:05:02Z
dc.date.available2024-09-29T16:05:02Z
dc.date.issued2023
dc.departmentKarabük Üniversitesien_US
dc.description.abstract17-4PH steel, which has the perfect combination of corrosion resistance and high mechanical properties, is especially preferred in defense and aerospace applications, but its machinability is poor. Thus, an extensive research has been conducted on its milling under sustainable cutting regimes (dry and minimum quantity lubrication_MQL) to contribute to both more efficient use and sustainable machining. First, the changes in resultant cutting force (Fr), the average surface roughness (Ra), the mean roughness depth (Rz) and total energy consumption (Pc-T) were investigated after the experiments performed by applying the L-18 orthogonal array. Subsequently, machining conditions were optimized for the minimization of machinability indicators with the Taguchi-based grey relational analysis technique. Finally, the predictive models for these indicators were developed by regression analysis. The order of importance for Fr and Pc-T was the depth of cut and feed, while for Ra and Rz this ordering was found to be feed rate and cutting regime. Short curved chips formed in MQL cutting regime contributed positively to the minimization of the considered machinability indicators. Although the energy consumption due to spindle speed increased with increasing cutting speed in dry cutting environment, the decrease in material strength resulted in a decrease in Pc-T. Since the cooling effect of MQL reduces the cutting temperature, material softening and thus the expected decrease in cutting resistance could not be achieved, so the decrease in Pc-T was not as much as dry cutting. Optimum machining conditions were determined as MQL cutting regime, the cutting speed of 120 m/min, the cutting depth of 0.5 mm and feed rate of 0.05 mm/rev. The determination coefficients of the predictive models developed by regression analysis showed that these models can be used safely in up milling.en_US
dc.identifier.doi10.1177/09544089231189640
dc.identifier.issn0954-4089
dc.identifier.issn2041-3009
dc.identifier.scopus2-s2.0-85166514567en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1177/09544089231189640
dc.identifier.urihttps://hdl.handle.net/20.500.14619/6467
dc.identifier.wosWOS:001039574500001en_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 E-Journal of Process Mechanical Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMillingen_US
dc.subjectstainless steelen_US
dc.subjectsurface roughnessen_US
dc.subjectcutting forceen_US
dc.subjectMQLen_US
dc.subjectenergy consumptionen_US
dc.subjectoptimizationen_US
dc.titleInvestigation of machinability indicators during sustainable milling of 17-4PH stainless steel under dry and MQL environmentsen_US
dc.typeArticleen_US

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