Determination of the optimal milling feed direction for unidirectional CFRPs using a predictive cutting-force model

To minimize the cutting force during milling of unidirectional carbon-fiber-reinforced plastics (CFRPs), we present a method that uses a predictive cutting-force model to optimize the feed direction. A CFRP with six different absolute fiber-orientation angles was used to derive specific cutting forces. Cutting force was predicted using regression of the specific cutting force and verified by milling tests, with 2-10-mm radial depths of cut at each fiber-orientation angle. The fiber cutting angle, which significantly affects CFRP cutting characteristics, can easily be changed by varying the feed direction. Therefore, the optimal feed direction is derived by predicting the cutting force in the feed direction in the range 0-180 degrees using the cutting-force model and comparing the cutting forces in all feed directions. The optimal feed direction is expressed by a second-order polynomial function of the radial depth of cut. In the validation of the proposed method, the cutting force and cycle time in the optimal feed direction were reduced by 54% and 53%, respectively. Because only the feed-direction angle is changed, which is a relatively easy adjustment in the milling process, this method efficiently reduces the cutting force in CFRP milling. Also, as a predictive cutting-force model is employed, it is possible to derive the optimal feed direction under various cutting conditions with minimal experimentation.

Automated summary

This paper presents a method that utilizes a predictive cutting-force model to optimize the feed direction during milling of CFRPs. By predicting and verifying cutting forces, the optimal feed direction is determined, resulting in reduced cutting force and cycle time. The proposed method offers an efficient way to minimize cutting force in CFRP milling, and allows for the derivation of the optimal feed direction under different cutting conditions with minimal experimentation.