Optimization of injection molding process parameters based on GA-ELM-GA

The most common optimization method for the of injection mold process parameters is range analysis, but there often a nonlinear coupling relationship between molding and quality indicators. Therefore, it difficult to find optimal combination in analysis. In this article, genetic algorithm optimized extreme learning machine network model (GA-ELM) combined with (GA) was proposed optimize mold. Take parameter an electrical appliance buckle cover shell as example. order corresponding minimum warpage deformation, orthogonal experiment designed results were analyzed. Then, degree influence on deformation obtained. At same time, by used predict plastic part. trained GA-ELM can map non-linear five well. And searched powerful ability algorithm. Generally speaking, after analysis reduced 6.7% compared experiment. But optimization, GAELM-GA 22%, which better than that thus verifying feasibility method. This provides certain theoretical reference technical support field involving parameters.