Intelligent predictive temperature control using PSO-RGA for transfer mold heating processes in semiconductor die packaging machines

This paper presents an intelligent predictive PI temperature control using particle swarm optimization - real coded genetic algorithm (PSO-RGA) for transfer molding modules in semiconductor die packaging machines. The system parameters of the transfer molding process are obtained by using the well-known reaction curve method. The best control parameters of the PI controller are offline tuned by using PSO-RGA algorithm. The set-point tracking, disturbance rejection, and robustness capabilities of the proposed method are well exemplified by conducting simulations and experiments on a real transfer mold process.