【摘要】 以家用空调遥控器前壳注塑件为例,在应用CAE模流分析确定塑件浇注系统和冷却系统的基础上,选取模具温度、熔体温度、注塑时间、保压时间和保压压力为设计变量,通过集成有限元模拟、Taguchi正交试验、BP神经网络(BPNN)以及粒子群优化算法(PSO)等来实现对薄壁塑件翘曲变形量的优化。优化后的工艺参数使得塑件翘曲变形量较优化前减少了37%,并应用Moldflow对优化工艺参数可靠性进行了模拟验证,结果显示,验证值和优化结果吻合度高,仅相差0.015 mm,表明所采用的薄壁塑件翘曲变形优化方法能显著减少注塑工艺参数调控过程对操作人员的经验依赖,具有较高的工程应用价值。更多还原

【Abstract】 The remote control front shell of the household appliance air conditioner was took as an injection molded part example,the injection system and cooling system of the plastic part was determined based on the application of CAE mold flow analysis,the mold temperature,melt temperature,injection time,holding pressure time,and holding pressure were selected as the design variables.The warpage deformation optimization result of the thin wall injection molded part was achieved by integrated finite element simulation,Taguchi method,BP neural network (BPNN) and particle swarm optimization (PSO) methods.The plastic part warpage deformation is reduced by 37% after optimization,and the optimization result reliability is verified by the Moldflow simulation analysis as well,the analysis result shows that the verification result and the optimized result are in good agreement,with a difference of only 0.015 mm,which indicates that the experience dependence of the injection process parameter adjustment process on the operator can be significantly reduced by the proposed optimization design method,and this optimization method has a high engineering application value.更多还原