针对汽车外饰薄壁零件生产中的多个工艺目标优化难题,本文以汽车 B 柱外饰件为分析对象进行研究.通过Moldflow软件建立零件仿真模型,并进行最优拉丁超立方试验采样数据,利用Kringing方法建立代理模型,以翘曲变形量和体积收缩率为注塑工艺的多个优化目标,通过邻域培植遗传算法(NCGA)对所建代理模型进行参数优化,并获得平衡了翘曲变形量和体积收缩率这 2 个目标的最优工艺参数组合:模具温度44.43℃,熔体温度205.36℃,注射时间1.99 s,保压压力38.71 MPa,保压时间27.47 s.与原有工艺参数相比,翘曲变形量降低了18.56%,体积收缩率降低了50.94%,注塑件质量得到显著提高.
Multi-objective Optimizations of the Injection Molding Process Parameters for Automotive Exterior Parts Based on NCGA
To solve the multi-objective optimization problems in the production of thin-walled exterior automotive parts,this article focused on the analysis of automotive B-pillar exterior parts.The simulation models of the parts were established using Moldflow software.The data was conducted by using the optimal Latin hypercube test.The Kringing method was used to establish a surrogate model with the warpage deformation and shrinkage rate as the multiple optimization targets for the injection molding process.The parameters of the surrogate model were optimized using the neighborhood cultivation genetic algorithm(NCGA).The results show that the optimal process parameter combination that balances the warpage deformation and shrinkage rate is as follows:a mold temperature of 44.43℃,a melt temperature of 205.36℃,an injection time of 1.99 s,a holding pressure of 38.71 MPa,and a holding time of 27.47 s.Compared with the original process parameters,the warping deformation is reduced by 18.56%,the volume shrinkage rate is reduced by50.94%,and the qualities of the injection molded parts are significantly improved.
万方数据
维普
