Abstract: 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.

Key words: rapid heat cycle molding, numerical simulation, optimal design, Kriging meta-model, genetic algorithm

摘要： 为了提高高光无痕注塑成型(rapid heat cycle molding,RHCM)制品综合品质,提出了一种基于Kriging模型与遗传算法(genetic algorithm,GA)结合的工艺参数优化策略.将该策略应用于某空调柜机出风面板成型,以正交实验法规划实验,通过CAE分析获取实验样本数据,借助数据归一化法、线性加权法、直观分析法等数据处理方法,得到了对RHCM成型影响显著的工艺参数依次为保压时间、冷却时间、熔体温度、加热时间.然后引入Kriging建模理论,建立了RHCM成型制品综合品质与主要成型工艺参数的近似模型,采用GA对建立的近似模型在可行解空间搜寻最优解.得到的最优工艺参数为:加热时间36.9 s,熔体温度182.9℃,保压压力88.5 MPa,冷却时间51.3 s.最后,通过CAE分析和生产试制分别验证了该优化策略的可行性和合理性.

关键词: 高光注射成型, 数值模拟, 优化设计, Kriging模型, 遗传算法