A comprehensive approach to determining minimum cutter lengths for five-axis milling

Interference detection and avoidance by the shortest cutter for the five-axis milling machining is a critical task. Short tool length increases the rigidity and chatter stability of the cutter. In this research, a new and efficient method of interference detection and avoidance by the shortest cutter is developed. For the specific five-axis machine configuration, first possible candidate parts for the collision are found, which are complete cutting system (spindle, tool holder, and cutter), the work in process model, and the fixture. Spindle, tool holder, and tool are represented by the solid geometry identity of the cylinder, truncated cone, and cylinder, respectively, with the length and diameter as parameters. The surfaces of the work in process model and the fixture model are represented as the point cloud data of the suitable density. The Kd-tree data structure is employed on point cloud data which gives an efficient searching of the potential candidate points for the interference detection with the complete cutting system. All existing methods are able to detect the collision, but they are not capable to remove it with the optimum cutter length. The proposed algorithm has not only the capability of collision detection; it can also remove the collision with the optimum tool length. Other scope of the proposed algorithm is the selection of the tool holder to minimize the overhang tool length.