A holistic research based on RSM and ANN for improving drilling outcomes in Al-Si-Cu-Mg (C355) alloy

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dc.authoridBAYRAKTAR, Senol/0000-0001-8226-0188
dc.contributor.authorBayraktar, Senol
dc.contributor.authorAlparslan, Cem
dc.contributor.authorSalihoglu, Nurten
dc.contributor.authorSarikaya, Murat
dc.date.accessioned2025-03-23T19:41:00Z
dc.date.available2025-03-23T19:41:00Z
dc.date.issued2025
dc.departmentSinop Üniversitesi
dc.description.abstractThe unique properties of Al-Si-based alloys make them suitable for components that demand structural integrity and wear resistance. This study was conducted to investigate the microstructure, mechanical, and drilling properties of a commercial alloy belonging to the Al-Si casting alloy group and containing approximately 4.5-5.5% Si (Al-5Si-1Cu-Mg). Drilling experiments were conducted with an 8 mm uncoated HSS (High-Speed Steel) drill across a range of cutting speeds (V) and feed rates (f) while maintaining a consistent depth of cut (DoC) parameters. Microstructural analysis using optical microscopy and SEM identified key phases within the alloy, including alpha-Al, eutectic Si, beta-Fe (beta-Al5FeSi), and pi-Fe (pi-Al8Mg3FeSi6) inter-metallics. Statistical analyses of the effects of V and f on thrust force (Fz), surface roughness (Ra), and torque (Mz) were performed using Response Surface Methodology (RSM), Artificial Neural Networks (ANN), and Analysis of Variance (ANOVA). The ANOVA results highlighted the significance of both V and f on the measured outputs, with optimal performance observed at a V of 125 m/min and f of 0.05 mm/rev (confidence level: 95%, P < 0.05). Additionally, predictive models based on RSM and ANN were developed for Fz, Ra, and Mz.
dc.description.sponsorshipPolish National Agency for Aca-demic Exchange (NAWA) under the Ulam Programme [02024009018075]; [BPN/ULM/2023/1/00035]
dc.description.sponsorshipThe authors would like to thank TUBITAK for their support with Project No: 221M064. Additionally, this study has been supported by the Recep Tayyip Erdogan University Development Foundation (Grant number: 02024009018075) .Murat Sar & imath;kaya acknowledges the Polish National Agency for Academic Exchange (NAWA) under the Ulam Programme (Grant No. BPN/ULM/2023/1/00035) .r number: 02024009018075) . Murat Sar & imath;kaya acknowledges the Polish National Agency for Aca-demic Exchange (NAWA) under the Ulam Programme (Grant No. BPN/ULM/2023/1/00035) .
dc.identifier.doi10.1016/j.jmrt.2025.01.115
dc.identifier.endpage1607
dc.identifier.issn2238-7854
dc.identifier.issn2214-0697
dc.identifier.scopus2-s2.0-85215401398
dc.identifier.scopusqualityQ1
dc.identifier.startpage1596
dc.identifier.urihttps://doi.org/10.1016/j.jmrt.2025.01.115
dc.identifier.urihttps://hdl.handle.net/11486/6489
dc.identifier.volume35
dc.identifier.wosWOS:001410712000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofJournal of Materials Research and Technology-Jmr&T
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250323
dc.subjectAl-Si alloy
dc.subjectDrilling
dc.subjectMachining
dc.subjectBuilt up-edge
dc.subjectOptimization
dc.subjectRSM
dc.subjectANN
dc.titleA holistic research based on RSM and ANN for improving drilling outcomes in Al-Si-Cu-Mg (C355) alloy
dc.typeArticle

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