Modelling surface roughness in finish turning as a function of cutting tool geometry using the response surface method, Gaussian process regression and decision tree regression

In this study, the modelling of arithmetical mean roughness after turning C45 steel was performed. Four parameters cutting tool geometry were varied, i.e.: corner radius r, approach angle κ, rake γ and inclination λ. After turning, Ra measured. The obtained values ranged from 0.13 μm to 4.39 μm. results experiments showed that surface improves with increasing radius, angle, decreasing angle. Based on experimental results, models developed predict distribution using response method (RSM), Gaussian process regression two kernel functions, sequential exponential function (GPR-SE) Mattern (GPR-Mat), decision tree (DTR). maximum percentage errors 3.898 %, 1.192 1.364 0.960 % for DTR, GPR-SE, GPR-Mat, RSM, respectively. worst case, absolute 0.106 μm, 0.017 0.019 0.011 show can be successfully used prediction.