Eaysin, AbdullahKabir, SarowerGünister, EbruJahan, NurHamza, AmirZinnah, Muhammad AliBin Rashid, Adib2024-11-292024-11-292025Eaysin, 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.2024.1003572666-8459https://doi.org/10.1016/j.rsurfi.2024.100357https://hdl.handle.net/20.500.13055/859AISI 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.eninfo:eu-repo/semantics/openAccessAISI P20Laser Beam Machine (LBM)Surface RoughnessKerf WidthAdaptive Neuro-Fuzzy Interface System (ANFIS)Brute ForceArticle10.1016/j.rsurfi.2024.100357181102-s2.0-85210069421Q3