Process parameter optimization of laser beam machining for AISI -P20 mold steel using ANFIS method

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dc.authorid0009-0003-5564-2115
dc.authorid0000-0002-4813-4361
dc.authorid0000-0002-7797-604X
dc.authorid0009-0006-3835-8691
dc.authorid0000-0002-1680-0729
dc.authorid0000-0002-0681-7383
dc.contributor.authorEaysin, Abdullah
dc.contributor.authorKabir, Sarower
dc.contributor.authorGünister, Ebru
dc.contributor.authorJahan, Nur
dc.contributor.authorHamza, Amir
dc.contributor.authorZinnah, Muhammad Ali
dc.contributor.authorBin Rashid, Adib
dc.date.accessioned2024-11-29T13:07:44Z
dc.date.available2024-11-29T13:07:44Z
dc.date.issued2025
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Makine Mühendisliği Bölümü
dc.description.abstractAISI P20 mold steel is commonly used for injection molds to produce plastic materials, car accessories, and electronic equipment molds. This study employed a fiber laser beam for precise machining of AISI P20 mold steel. The experimental design, based on the Taguchi 27 model, was carried out using Minitab software to optimize machining parameters, including cutting speed, gas pressure, and laser power. Surface roughness (Ra) and kerf width were the response parameters investigated. The ANFIS model, developed and analyzed using MATLAB, successfully predicted response parameters and was experimentally validated, showing improved predictions over actual measurements. The Brute Force algorithm identified the minimum combination for an optimal parameter set. The Taguchi method determined the best process parameters, indicating that cutting speed had the most significant impact. The optimum Ra was achieved with 1 m/min cutting speed, 2 bar gas pressure, and 1.8 kW laser power, while the lowest kerf width was obtained with 2 bar gas pressure, 1 m/min cutting speed, and 1.9 kW laser power. Based on the Brute Force algorithm, the minimum combination resulted in a kerf width of 0.84 mm and a surface roughness of 4.48175 μm. Microstructural analysis was performed on samples with high and low surface roughness to assess the machining surface quality.
dc.identifier.citationEaysin, A., Kabir, S., Günister, E., Jahan, N., Hamza, A., Zinnah, M. A., & Bin Rashid, A. (2025). Process parameter optimization of laser beam machining for AISI -P20 mold steel using ANFIS method. Results in Surfaces and Interfaces, 18, pp. 1-10. https://doi.org/10.1016/j.rsurfi.2024.100357
dc.identifier.doi10.1016/j.rsurfi.2024.100357
dc.identifier.endpage10
dc.identifier.issn2666-8459
dc.identifier.scopus2-s2.0-85210069421
dc.identifier.scopusqualityQ3
dc.identifier.startpage1
dc.identifier.urihttps://doi.org/10.1016/j.rsurfi.2024.100357
dc.identifier.urihttps://hdl.handle.net/20.500.13055/859
dc.identifier.volume18
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynak.otherESCI - Emerging Sources Citation Index
dc.institutionauthorGünister, Ebru
dc.institutionauthorid0000-0002-7797-604X
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofResults in Surfaces and Interfaces
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAISI P20
dc.subjectLaser Beam Machine (LBM)
dc.subjectSurface Roughness
dc.subjectKerf Width
dc.subjectAdaptive Neuro-Fuzzy Interface System (ANFIS)
dc.subjectBrute Force
dc.titleProcess parameter optimization of laser beam machining for AISI -P20 mold steel using ANFIS method
dc.typeArticle
dspace.entity.typePublication

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