A novel surface quality evaluation method in ultra-precision raster milling using cutting chips

Although online surface quality evaluation is important in ultra-precision machining technologies, very little research has been reported on the topic. In this paper, cutting chips were employed to evaluate machined surface quality online under the occurrence of tool wear in ultra-precision raster milling. Cutting chips were collected and examined by a 3D scanning electron microscope. The inspected cross-sectional shape of 'ridges' imprinted by the tool fracture was approximated into two geometric elements so that it could be determined by a mathematical model. The geometric elements for every ridge were assembled into a virtual cutting edge so as to rebuild the machined surface. A mathematical model was established to realize the rebuilt machined surface and calculate the surface roughness under the consideration of tool fractures effects. The theoretical and experimental results show that the ridges imprinted on the machined surface can be predicted by examining a section of the collected cutting chips. It is interesting to note that the quality of the machined surface is reflected in the location and the height of ridges. This demonstrates that the online surface quality evaluation using cutting chips is a novel method as compared to conventional methods, since it can evaluate the machined surface and simulate the machined surface topography without the need to stop the cutting process.