ALGORITHMS AND DATA STRUCTURES FOR FAST SURFACE QUALITY ESTIMATION IN MILLING

New approaches for fast surface quality estimation in Milling are presented. Dimensional Error, Surface Roughness, and the 3D topological plots of the surfaces are generated. Calculation speed is improved by methods of structural organization and numerical optimizations. Structural organization enables program division into initialization and program-run segments for faster runs. Numerical optimizations are used to help further reduce the run time by reducing variable volume and avoiding unnecessary estimations. Experimental evaluation of the methods for Dimensional Error, Surface roughness and profiles are performed using three different cutting tool types (flat-end, ball-end and insert mills) in order to reveal strengths and weaknesses of the proposed approaches. Comparison of experimental and estimated surface profiles show good correlation. Typical surface profile estimation for one tool rotation takes between 0.04-4.1 seconds depending on the cut and whether or not the tool deflection is included in the algorithm. Surface quality estimation is done quickly enough to be promising for use in feedrate scheduling. Further improvement in the tool deflection model is expected to increase accuracy and further reduce the computational time.