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The present study is aimed for an optimization strategy for the CNC pocket millingprocess based on the desirability function approach (DFA) combined with the response surface methodology (RSM). Firstly, the milling parameters such as cutting speed, feed rate and depth of cut are designed using the rotatable central composite design (CCD). The AISI 1050 medium carbon steel is machined by a flat end 8 mm high speed steel (HSS) tool on a zigzag cutting path under air flow condition. The influence of milling parameters is examined. Secondly, the model for the surface roughness, as a function of milling parameters, is obtained using the RSM. Finally, the power and adequacy of the quadratic mathematical model has been proven by the analysis of variance (ANOVA) method. The results indicate that the feed rate is the dominant factor affecting the surface roughness, which is minimized when the feed rate and depth of cut are set to the experimental range. A high correlation coefficient of R 2  = 0.99 has been obtained between the predicted and the experimental surface roughness. This reveals that the prediction system established in this study produces satisfactory results with an improved performance compared to other models in the literature. The enhanced method proposed in this study can be readily applied to different metal cutting processes with greater confidence.

Surface roughness analysis and optimization for the CNC milling process by the desirability function combined with the response surface methodology