GPU-based Optimization of Tool Path Planning in 5-Axis Flank Milling

5-axis machining technology has received much attention since the late 90’s. It offers better machining efficiency and superior shaping capability compared with 3-axis machining. Machining error control is considered to be a challenging task in 5-axis flank milling of complex geometries. Previous studies have shown that optimized tool path planning is a feasible approach to reduction of the machining error. However, the error estimation is very time-consuming in the optimization process, thus limiting the practicality of the approach. In this work, we apply GPU computing technology to solve this problem. A PSO-based optimization scheme is developed to generate a series of cutter locations corresponding to a globally minimized machining error. The error induced by each cutter location is simultaneously calculated by the parallel processing units in GPU. This significantly accelerates the search process in the optimization scheme, while the optimal solution remains the same as that obtained by CPU. Our test result demonstrates the potential of improving the computational efficiency in CAD/CAM using GPU.