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This study investigates the influence of key machining parameters on the surface roughness (Ra) during external cylindrical milling of hardened 90CrSi tool steel using a minimum quantity lubrication (MQL) system enhanced with CuO nanoparticles (Nano-MQL). A blocked and modified Box-Behnken-based design was employed to systematically evaluate the effects of five input variables: tool diameter (Dt), cutting speed (vc), feed per tooth (fz), depth of cut (ap), and nanoparticle size (Davg). A second-order regression model was developed based on response surface methodology (RSM), yielding a high predictive accuracy with an R2 value of 0.9156. The analysis revealed that fz, ap, and vc had the most significant effects on Ra, while Davg exhibited minimal impact. The optimal surface finish (Ra = 0.0728 μm) was obtained at vc = 150 m/min, fz = 0.0200 mm/tooth, ap = 0.080 mm, Dt = 12 mm, and Davg = 100 nm. These findings offer practical guidance for achieving superior surface quality in hard milling processes under sustainable lubrication conditions.

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Statistical Modeling and Optimization of Surface Roughness in Nano-MQL Milling of Hardened 90CrSi Cylindrical Surfaces

  • 会议论文

  • 发表日期：

    2026年

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  • Dinh Van Thanh,
  • Hoang Van Got,
  • Do The Vinh,
  • Vu Ngoc Pi,
  • Hoang Anh Toan

摘要

This study investigates the influence of key machining parameters on the surface roughness (Ra) during external cylindrical milling of hardened 90CrSi tool steel using a minimum quantity lubrication (MQL) system enhanced with CuO nanoparticles (Nano-MQL). A blocked and modified Box-Behnken-based design was employed to systematically evaluate the effects of five input variables: tool diameter (Dt), cutting speed (vc), feed per tooth (fz), depth of cut (ap), and nanoparticle size (Davg). A second-order regression model was developed based on response surface methodology (RSM), yielding a high predictive accuracy with an R2 value of 0.9156. The analysis revealed that fz, ap, and vc had the most significant effects on Ra, while Davg exhibited minimal impact. The optimal surface finish (Ra = 0.0728 μm) was obtained at vc = 150 m/min, fz = 0.0200 mm/tooth, ap = 0.080 mm, Dt = 12 mm, and Davg = 100 nm. These findings offer practical guidance for achieving superior surface quality in hard milling processes under sustainable lubrication conditions.