The focus of this paper is to present a reliable method to predict flank wear during milling process. A neural-fuzzy scheme is applied to perform the prediction of flank wear from cutting force signals. The experimental results indicate that the proposed ANFIS model has a high accuracy for estimating flank.
COBISS.SI-ID: 12348438
The paper presents the model based mechanism of control assuring constant quality of surface finish by controlling the cutting forces in the end milling process. By dynamic adaptation of feeding and speed the system controls the surface roughness and the cutting forces on the milling cutter.
COBISS.SI-ID: 12406806