Machining and Sustainability Performance Comparison for the Milling Process of Al6082 Alloy Under Various Minimum Quantity Lubrication Conditions

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dc.contributor.authorYapan, Yusuf Furkan
dc.contributor.authorTurkeli, Kerim
dc.contributor.authorEmiroglu, Ugur
dc.contributor.authorBahce, Erkan
dc.contributor.authorUysal, Alper
dc.date.accessioned2026-04-04T13:35:17Z
dc.date.available2026-04-04T13:35:17Z
dc.date.issued2025
dc.departmentİnönü Üniversitesi
dc.description.abstractAluminum 6082 alloys are commonly utilized in significant industries because of their unique characteristics. However, they exhibit poor machinability as a result of their high ductility, high thermal expansion coefficient, and tendency to built-up edge formation. Considering the alloy's widespread usage, the difficulty of machining it raises sustainability concerns. For this reason, although minimum quantity lubrication (MQL) methods using various nanoparticle-added nanofluids have been used to enhance machinability, the use of graphene nanoparticles (GNP) has been ignored. Furthermore, there has been a lack of sustainability assessment and optimization. In the presented study, MQL methods using various GNP-added nanofluid (N-MQL) was used for the first time in the milling of Al6082 alloy, and its machining responses (cutting temperature, cutting force, feed force, surface roughness, and chip morphology) and sustainability indicators (carbon emission and total machining cost) were determined and compared with dry-cutting and pure MQL utilizing vegetable cutting oil. The utilization of the N-MQL, as opposed to the dry-cutting with appropriate cutting parameters, resulted in improvements of 50.6% in cutting force, 65.4% in feed force, 50.6% in cutting temperature, 33.2% in chip width, 15.3% in chip length, 67.3% in surface roughness, 21.5% in carbon emissions, and 52.6% in machining cost. Finally, applying multi-objective optimization using NSGA-II (non-dominant sequencing genetic algorithm II) and the multi-criteria decision-making method using VIKOR, optimum process parameters were determined in terms of sustainability-weighed carbon emissions and total machining cost. From the sustainability-based optimization results, it was determined that the cutting speed should be selected between 36 and 40 m/min, the feed should be selected between 0.14 and 0.18 mm/rev, and the N-MQL method should be used. Using the N-MQL method at above-average cutting speeds and feed values are the most sustainable machining parameters and condition for milling of Al6082.
dc.identifier.doi10.1007/s40684-024-00655-3
dc.identifier.endpage430
dc.identifier.issn2288-6206
dc.identifier.issn2198-0810
dc.identifier.issue2
dc.identifier.orcid0000-0001-5389-5571
dc.identifier.orcid0000-0001-9684-4117
dc.identifier.scopus2-s2.0-85201428330
dc.identifier.scopusqualityQ1
dc.identifier.startpage409
dc.identifier.urihttps://doi.org/10.1007/s40684-024-00655-3
dc.identifier.urihttps://hdl.handle.net/11616/109744
dc.identifier.volume12
dc.identifier.wosWOS:001292341300001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherKorean Soc Precision Eng
dc.relation.ispartofInternational Journal of Precision Engineering and Manufacturing-Green Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250329
dc.subjectGraphene nanofluid
dc.subjectMinimum quantity lubrication
dc.subjectMachining responses
dc.subjectSustainability analysis
dc.titleMachining and Sustainability Performance Comparison for the Milling Process of Al6082 Alloy Under Various Minimum Quantity Lubrication Conditions
dc.typeArticle

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