Optimization of milling parameters of thin-walled parts based on improved firework algorithm

In view of the problem that thin-walled parts are easily deformed by force during the milling process, the internal iterative process is improved using the firework algorithm (FWA) as the basic model, and an improved firework with higher calculation efficiency and more accurate results is proposed. Algorithm (IFWA) combined with improved fireworks algorithm and BP neural network to optimize the milling parameters of thin-walled parts. The simulation results show that, compared with the PSO-BP algorithm and the GA-BP algorithm, the thin-walled parts processed by the milling parameters obtained by the IFWA-BP algorithm have a smaller amount of deformation, and the field machining experiments further prove that the IFWA-BP algorithm Milling parameters are optimized for accuracy and reliability.