Akademik Veri Yönetim Sistemi
ENGINEERING SCIENCE AND TECHNOLOGY, AN INTERNATIONAL JOURNAL, cilt.79, 2026 (SCI-Expanded, Scopus)
Fiber laser cutting has been utilized as a common manufacturing process as it is capable to create accurate shapes with high product yield and very low thermal distortion. Nonetheless, the type and efficiency of laser-cut components are highly impacted by appropriate choice of cutting parameters. The current paper showed the effect of cutting speed, assist gas pressure, and focal position on hole quality and energy consumption of fiber laser cutting of AISI 430 ferritic stainless steel. The experiments were developed based on Taguchi L27 orthogonal array and the response parameters adopted are diameter deviation (Dd), surface roughness (Ra), dross height (Dh) and energy consumption (Ec). Taguchi-based grey relational analysis (TGRA) was used to simultaneously optimize multi-response characteristics. Increasing the assist gas pressure increased the melt ejection rate and significantly reduced dross formation. Increasing the cutting speed caused unstable melt ejection due to the high thermal conductivity of the ferritic steel, increasing roughness while reducing energy consumption. According to variance analysis, focal position is the most effective parameter for diameter deviation, cutting speed for surface roughness and dross height, and gas pressure for energy consumption. SEM observations clearly showed that the flow characteristics of the molten material and the resulting hole surface morphology changed according to the selected process parameters. Based on the multi-response optimization, the best cutting performance was obtained at −4 mm focal position, 1200 mm/min cutting speed and 18 bar gas pressure. For simultaneous minimization of the considered responses, gas pressure was determined to be the most effective parameter with approximately 62%. The coefficients of determination (R2 > 94% yada over 94%) calculated for the developed regression models show that responses in laser cutting of ferritic stainless steel can be predicted reliably and with high accuracy.