Roughness control method for five-axis flank milling based on the analysis of surface topography

In five-axis flank milling, the surface roughness always varies within a relatively large scale due to the variable geometric feature of the non-developable ruled surface. This variation in roughness is an unstable factor that leads to poor machining quality at local positions on the machined surface. To solve these problems, this paper presents a surface roughness control method using feed rate optimization for five-axis flank milling based on the analysis of surface topography. First, the surface topography is predicted by a novel elliptical model. Based on this model, the influences of cutter runout and workpiece curvature on the surface profile height are analysed. Then, the surface roughness is expressed as a function of the local curvature at each cutting location. Finally, an overdetermined system of nonlinear equations is derived that allows the feed rate to be adjusted for providing an even roughness distribution on the machined surface. A series of cutting tests are performed to validate the proposed theory. The results show that the roughness uniformity and machining quality of the surface are effectively improved by the optimized feed rate.