基于计算机辅助技术的油污传感器注塑成型工艺优化

Injection Molding Process Optimization of Oil Pollution Sensor Based on Computer Aided Technology

针对某30%玻纤增强PA66的油污传感器,利用Moldflow模拟注塑成型过程,并设计正交试验探究低翘曲与低质量的优化工艺组合。依据流动阻力、浇口匹配性结果确定最佳的浇口位置为产品中部。各工艺参数对最大翘曲变形量的影响程度排序为:熔体温度>保压压力>注射时间>模具温度>v/p切换体积>保压时间;对质量的影响程度排序为:保压时间>模具温度>保压压力>v/p切换体积>注射时间>熔体温度。综合分析得到优化的工艺参数组合为A;B;C;D;E;F;。与初始参数相比,基于优化工艺分析得到的最大翘曲变形量及质量分别降低36.7%和15.4%,且满足设计要求,通过实际试模验证为可用。

For a 30% glass fiber reinforced PA66 oil pollution sensor, Moldflow was used to simulate the injection molding process, and orthogonal tests were designed to explore the optimal process combination of low warpage and low mass. According to the results of flow resistance and gate matching, the best gate location was determined at the middle of the product. The influence degree of each process parameters on the maximum warpage deformation is as follows: melt temperature>holding pressure>injection time>mold temperature>v/p switching volume>holding time. The order of influence on mass is: holding time>mold temperature>holding pressure>v/p switching volume>injection time>melt temperature. Through comprehensive analysis, the optimized process parameter combination is A;B;C;D;E;F;. Compared with the initial parameters, the maximum warpage deformation and mass obtained based on the optimized process analysis are reduced by 36.7% and 15.4% respectively, and meet the design requirements. It is verified to be available through the actual mold test.