Yayın:
Orthogonal turning of AISI 310S austenitic stainless steel under hybrid nanofluid-assisted MQL and a sustainability optimization using NSGA-II and TOPSIS

dc.contributor.authorSaatci, Emirhan
dc.contributor.authorYapan, Yusuf Furkan
dc.contributor.authorUysal, Mine Uslu
dc.contributor.authorUysal, Alper
dc.date.accessioned2026-06-27T14:52:38Z
dc.date.issued2023
dc.description.abstractAISI 310S austenitic stainless steels are widely used in many industries, such as oil, gas, and petrochemical industries containing hot concentrated acids, due to their superior properties like corrosion resistance, high-temperature service, and creep resistance. However, a study on the machining of AISI 310 stainless steel has not been published in the scientific literature. It is known that the machinability of the austenitic stainless steel alloys, in which the AISI 310S alloy is included, is poor due to its low thermal conductivity, high work hardening, and built-up edge (BUE) formation. This situation causes sustainability problems by increasing the energy consumptions, the total machining cost and the amount of carbon emissions. The presented study investigated for the first time machining response and sustainability assessment in the orthogonal turning of AISI 310S stainless steel using three different cutting speeds and feed values, and five different cutting conditions such as dry, vegetable-based fluid minimum quantity lubrication (MQL), nano molybdenum disulfide (nMoS2) reinforced nanofluid MQL, nanographene (nGP) reinforced nanofluid MQL, and nMoS2/nGP reinforced hybrid nanofluid MQL, and a sustainability optimization was performed. Sustainability optimization was conducted to minimize the resultant force, surface roughness, carbon emission, and total machining cost using multi-objective optimi-zation with NSGA-II (Non-dominated Sorting Genetic Algorithm II) and multi-criteria decision-making with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). The resultant force, surface roughness, total carbon emission, and total machining cost were reduced by a significant, 56.8%, 86.8%, 30.4%, and 2.9%, respectively, under the nGP reinforced nanofluid MQL cutting condition compared to the dry cutting condition. As a result of sustainability optimization, the use of high cutting speed (220 m/min), low feed values (between 0.11 mm/rev and 0.14 mm/rev), and nGP reinforced nanofluid MQL method (N2-MQL) in the turning of AISI 310S stainless steel material provides the optimum surface roughness values, cutting forces, carbon emissions, and total machining costs.en
dc.description.urihttps://doi.org/10.1016/j.susmat.2023.e00628
dc.identifier.doi10.1016/j.susmat.2023.e00628
dc.identifier.issn2214-9937
dc.identifier.urihttps://hdl.handle.net/20.500.14981/65725
dc.identifier.volume36
dc.identifier.wos001013092400001
dc.language.isoeng
dc.publisherELSEVIER
dc.relation.ispartofSUSTAINABLE MATERIALS AND TECHNOLOGIES
dc.subjectStainless steel
dc.subjectSustainable machining
dc.subjectSustainability assessment
dc.subjectSustainability optimization
dc.subjectGenetic algorithm
dc.subjectMachining response
dc.subjectCarbon emission
dc.subjectTotal machinig cost
dc.subjectMINIMUM QUANTITY LUBRICATION
dc.subjectSERRATED CHIP FORMATION
dc.subjectNANO-CUTTING FLUID
dc.subjectSLIP-LINE MODEL
dc.subjectSURFACE-ROUGHNESS
dc.subjectTOOL WEAR
dc.subjectHARDENED STEEL
dc.subjectCARBIDE TOOLS
dc.subjectPERFORMANCE
dc.subjectDRY
dc.subjectScience & Technology - Other Topics
dc.subjectEnergy & Fuels
dc.subjectMaterials Science
dc.titleOrthogonal turning of AISI 310S austenitic stainless steel under hybrid nanofluid-assisted MQL and a sustainability optimization using NSGA-II and TOPSIS
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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