Optimization of Injection Molding Process Parameters Based on Response Surface Methodology and Genetic Algorithm

摘要

In this paper,a number of injection molding CAE simulations were carried out according to the Latin Square orthogonal array by utilizing the method of Design of Experiment (DOE). These experimental data were used to build a surrogate model to identify the relationship between the injection molding process parameters and warpage using the Response Surface Methodology (RSM),with proper validation of the model accuracy. By using the surrogate model,the RSM and genetic algorithm (GA) were combined to find the optimal injection molding processing parameters. The results show that the developed surrogate model is accurate and reliable,and the optimization efficiency is largely improved by applying the RSM method,hence the combination of RSM and GA proposed in this paper is useful for the optimization of injection molding process parameters and for minimizing the molding warpage.