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An innovative hybrid optimization approach for sustainable milling of support structures in additively manufactured Ti-6Al-4V components utilizing NSGA-III and COBRA

dc.contributor.authorAkcadirci, Ahmet
dc.contributor.authorYapan, Yusuf Furkan
dc.contributor.authorAltan, Mihrigul Eksi
dc.contributor.authorKhan, Aqib Mashood
dc.contributor.authorUysal, Alper
dc.date.accessioned2026-06-27T15:20:36Z
dc.date.issued2025
dc.description.abstractProblems such as bending, collapsing, and therefore inability to cut occur in the cleaning of support structures used in additive manufacturing. For this reason, cleaning supports increases both costs and production time, as well as sustainability concerns due to the increasing work volume in the world of metal additive manufacturing. In addition, cleaning of support structures is usually performed manually by the operator, and since this situation can not provide the expected mechanical properties, precise surface, and dimensional tolerances from the part, the operator's effectiveness in the process must be reduced. For these reasons, there is a need to clean support structures successfully and sustainably. This study investigated the sustainable milling of additively manufactured as-built and annealed support structures from Ti-6Al-4V alloy using different feed values under dry, minimum quantity lubrication (MQL) with vegetable-based cutting oil and MQL with graphene nanoparticle-reinforced nanofluid (N-MQL) cutting conditions in terms of cutting force, energy consumption, and circumferential and areal damage. After that, a novel hybrid optimization was performed by combining the Non-dominated Sorting Genetic Algorithm III (NSGA-III) multi-objective optimization method and the Comprehensive Distance Based Ranking (COBRA) multi-criteria decision-making method. The N-MQL method improved the cutting force, energy consumption, circumferential damage, and areal damage by 15.2%, 0.086%, 18.4%, and 16.8%, respectively, compared to the dry cutting condition. It has been determined by the novel hybrid optimization that milling the as-built Ti-6Al-4V alloy support structure under the N-MQL cutting condition at a feed value of 0.05-0.0554 mm/rev is optimum in terms of both machining performance and sustainability. It has been concluded that cutting the support structures from the additively manufactured components before the annealing process is more appropriate, rather than annealing them simultaneously with the primary portion, then cutting.en
dc.description.sponsorshipNational Outstanding Youth Science Fund Project of National Natural Science Foundation of China
dc.description.urihttps://doi.org/10.1007/s00170-025-16356-3
dc.identifier.doi10.1007/s00170-025-16356-3
dc.identifier.eissn1433-3015
dc.identifier.endpage1352
dc.identifier.issn0268-3768
dc.identifier.issue3-4
dc.identifier.startpage1335
dc.identifier.urihttps://hdl.handle.net/20.500.14981/69964
dc.identifier.volume140
dc.identifier.wos001553763900001
dc.language.isoeng
dc.publisherSPRINGER LONDON LTD
dc.relation.ispartofINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
dc.subjectTi-6Al-4V
dc.subjectSupport structure
dc.subjectMinimum quantity lubrication
dc.subjectGraphene nanofluid, NSGA-III
dc.subjectCOBRA
dc.subjectMECHANICAL-PROPERTIES
dc.subjectFINISH
dc.subjectMACHINABILITY
dc.subjectBEHAVIOR
dc.subjectMQL
dc.subjectAutomation & Control Systems
dc.subjectEngineering
dc.titleAn innovative hybrid optimization approach for sustainable milling of support structures in additively manufactured Ti-6Al-4V components utilizing NSGA-III and COBRA
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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