Simulation and prediction of surface topography machined by ball-nose end mill

According to the definition of surface topography, it could be separated into two parts of macroscopic shape error and microscopic surface roughness. An integrated method which included geometric modeling and neural network was proposed to simulate and predict surface topography. By using the principles of transformation figure matrix and vector operation, the movement path equation of ball-nose end mill versus work-piece was derived. A simulation model for the three-dimensional surface topography generated by a ball-nose end mill was established, which could predict the shape error. By means of MATLAB software, the Back Propagation (BP) neural network prediction model for surface roughness was established. The accuracy of the simulation and prediction models was verified by experiments, which indicated the effective prediction for surface topography.