Processing parameters optimization of rapid heat cycle molding based on Kriging meta-model and genetic algorithm

In order to improve the comprehensive quality of high-gloss plastic part, an integrated optimization strategy based on Kriging meta-model and genetic algorithm (GA) was proposed. The optimization strategy was used to optimize the processing parameters of an air-conditioning panel plastics with rapid heat cycle molding (RHCM). Coupled with CAE analysis, the Taguchi method was used to arrange the experimental points. Through the normalization method, linear weighted method and intuitive analysis, it was found that packing pressure, cooling time, melt temperature and heating time were the significant process parameters which affected comprehensive quality of plastic part with RHCM. Then Kriging meta-model was introduced to establish a predictive model between comprehensive quality and the significant process parameters. Besides, GA was used to seek the best result of the predictive model in the feasible solution space. The optimal process parameters were heating time of 36.9 s, melt temperature of 182.9℃, packing pressure of 88.5 MPa, cooling time of 51.3 s. Finally, computer-aided engineering (CAE) analysis and actual production achieved good result, showing that the integrated optimization strategy was feasible and reasonable in processing quality optimization of high-gloss plastic part.