In this study, we conducted an interrupted cutting SM20C with lathe and uncoated carbite tool, determined the relationship between Cutting Forces(principal, radial, feed force) by correlation analysis, and predicted the optimum cutting conditions by multiple regression analysis. The result were as follow. : From the correlation analysis, the increase of cutting speed and depth of cut reduces the principal force and radial force. the increase of cutting speed, depth of cut and feed rate will increase the feed force. From multi-regression analysis, we extracted regression equation and the coefficient of determination (R2) was 0.638, 0.692, 0.536 at principal, radial and feed force . It means that the regression equation is not high accuracy. However, it is predictable that the tendency of the forces action the interrupted cutting.

In this study, we carried out interrupted cutting of carbon steel for machine structure(SM20C) with uncoated carbide tool and analyzed anova test and confidence interval to find influential factor to surface roughness, and obtained regression equation. Rhe results are follows: First, we found that affected factor to surface roughness in interrupted cutting was feed rate. Secondly, the cutting speed and depth of cut was small affected to surface roughness. Finally, from multi-regression analysis of interrupted cutting experimental result, obtained regression equation and it’s coefficient determination was 0.814 and it means that regression equation was predictable. Compared with other continuous cutting, if feed rate increase, surface roughness will grow in interrupted cutting.