Optimization of molding process parameters of fixed-axis injection mold based on NSGA-II genetic algorithm
In order to solve the problems of casting quality and casting inefficiency in the injection molding process,a novel injection process parameter optimization and screening method was proposed combining NSGA-II algorithm and TOPSIS method with the response surface method.With a fixed shaft as the object of study,Box-Behnken design was adopted,with melt temperature,mold temperature,injection time,holding pressure as variables,and product quality with warpage deformation amount and volume shrinkage as response variables.The NSGA-II genetic algorithm was used to perform optimization of the objective functions of the two responses,and then the optimal solution was found by solving the optimized Pareto front solution set using the TOPSIS method.The final simulation verification showed that when the injection time was 40.71 s,the mold temperature was 131℃,the melt temperature was 180.07℃,and the holding pressure was 65 MPa,the warpage deformation was reduced by 10.92%,while the volumetric shrinkage rate was reduced by 11.19%.The optimize and improve injection process parameters could effectively eliminate the defects of shrinkage loosening and shrinkage hole inside the casting,thus forming a dense casting with good performance,which could effectively improve the quality of products.
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