Optimizing end-milling parameters for surface roughness under different cooling/lubrication conditions

The effect of cutting parameters on average surface roughness (Ra) in the different cooling/lubrication conditions, including minimal quantity lubrication, wet and dry cutting, was analyzed in this study. Orthogonal arrays were applied in the design of experiments, and Ti6Al4V end-milling experiments were performed on the Daewoo machining center. The white light interferometer (Wyko NT9300) was used to obtain the 3D profile of machined surface and calculate Ra values. Then, exponential model and quadratic model were proposed to fit the experimental data of surface roughness, respectively. Exponential fit model was employed to determine the significant cutting parameters on average surface roughness. Quadratic fit model was used to optimize the cutting parameters when cutting tool and material removal rate were given. The optimal average surface roughnesses were estimated according to the quadratic model. Finally, the verification experiments were performed, and the experimental results showed good agreement with the estimated results.