Adaptive tool path planning strategy for freeform surface machining using point cloud

This paper reports the development of an efficient tool path planning strategy for machining of freeform surfaces directly from their representation in the form of point cloud without interim surface fitting. A grid based adaptive planar strategy has been designed and implemented for 3-axis CNC machining using ball end mill. Uniform CL grid points are initially computed by using tool inverse offset algorithm. Estimating the chordal and scallop errors likely to be produced, adaptive grid refinement is carried out iteratively till the errors converge below the prescribed tolerance limits. Adaptive grid (CL) points are subsequently processed to generate the final CNC part programs in the ISO format. The part programs were extensively tested for various case studies using the commercial CNC simulator as well on the actual CNC machine. Effects of variation of grid size and cloud point density were studied for grid optimality and their effect on the quality of CNC programs generated. The results were compared with those from the commercial software. Our system was found to generate more efficient tool paths in terms of enhanced productivity, part quality and reduced memory requirement.