Optimization of Forming Process Parameters for Fire Alarm Shell Based on Moldflow and BP Neural Network
Taking the fire alarm shell as the research object,the mold flow analysis of the shell was carried out in Moldflow software to seek the minimum warping deformation of the shell as the solu-tion result.The orthogonal experimental method was used to design the experimental plan,and the re-sults were analyzed for mean and range.The combination of various process parameters after the first optimization was obtained.On the basis of the first optimization,a BP neural network parameter model was established for the warping deformation of the shell,and the influence trend of injection molding process parameters on the warping deformation of the shell was determined.The maximum warping de-gree of the optimized shell was reduced by 11.3％.At this time,the optimal injection molding process parameters were mold temperature of 50 ℃,melt temperature of 205 ℃,injection time of 1.6 seconds,holding time of 16 seconds,and holding pressure of 95 MPa.Based on BP neural network,the warping value of plastic parts was predicted,and the prediction results showed that the accuracy of the predicted values was high,which can effectively improve the design efficiency and reliability of the mold.
fire alarm caseBP neural networkMoldflowprocess parameters
万方数据
维普
