Parallel Turning Process Parameter Optimization Based on a Novel Heuristic Approach

Process parameter optimization has been widely investigated in single-tool machining operations. However, for multitool machining operation optimization, the research reported in literature is scarce. In this paper, a novel heuristic algorithm based on particle swarm optimization (PSO) is proposed to optimize, in terms of minimum machining time, the process parameters for two-tool parallel turning operations with n features. Both single-pass and multipass operations are considered. The simulation results show that the performance of the proposed algorithm, in terms of total machining time and required computational time, is superior to an exhaustive search algorithm.