Particle swarm optimisation (PSO)-based tool path planning for 5-axis flank milling accelerated by graphics processing unit (GPU)

Abstract

Multi-axis machining offers higher machining efficiency and superior shaping capability compared to 3-axis machining. Machining error control is a critical issue in 5-axis flank milling of complex geometries and there is still a lack of solutions. Previous studies have shown that optimisation-based tool path planning is a feasible approach to reduction of machining error. However, the error estimation is time-consuming in the optimisation process, thus limiting the practicality of this approach. In this work, we apply graphics processing unit (GPU) computing technology to solve this problem. A particle swarm optimisation (PSO)-based optimisation scheme is developed to generate a series of cutter locations (CLs) that produce a minimised error on the machined surface. The error amount induced by each CL is simultaneously calculated by the parallel processing units of GPU. The PSO search process driven by the aggregated result is effectively accelerated. Test results show that our approach outperforms previous optimisation methods in both solution quality and computation efficiency. This work demonstrates a novel application of GPU on Computer Aided Manufacturing/Computer Numerical Control.