Numerical Simulation Research Of The Injection Molding For Thin-Wall Plastic Parts And Optimize Of The Process Parameter

Thin-wall injection molding technology is being developed rapidly on the basis of conventional injection molding technology.The thin-wall design can reduce the weight and external dimension of the products, shorten production molding cycles,economize material and lower costs,etc. But the thin-wall design reduce the formability of part,it is difficulty to control the quality of thin-wall parts.In this thesis,using the CAE software,numerical simulation research of the injection molding characteristic for thin-wall plastic parts are put forward,then analyse the warpage and shrinkage to optimize the parameter. The purpose is to offer the theory guidance for the production process parameter.The principal contents studied in this thesis are as follows:1)The thin-wall plastic injection processes of simplified shell part is simulated,selecting three materials:cycoloy C1200HFM,Lexan JK2500, PC/ABS,and selecting the various thickness:0.5mm,0.3mm,0.2mm.The effects of process parameters(melt temperature,mold temperature, injection pressure,injection rate)on molding characteristic of thin-wall plastic parts are discussed by single factor method,along with thickness reduction,compare the significance of each factors.2)Analyse the store ice barrel with short shots,select the material,optimize the gate,adjust the process parameters to solve the short shots question.3)Selecting thickness:2.0mm,1.5mm,1.0mm,0.5mm simplified shell parts, using the orthogonal experiment method to arrangement process parameters(melt temperature,mold temperature,injection rate,holding pressure,holding time,cooling time),and then simulating.The warpage and shrinkage date are analyzed using ANOVA.The results are used to compare the significance of each parameters with the various thickness,and obtain the optimum set of process parameters.4)Application of orthogonal experiment method and grey-fuzzy logic, composite the warpage and shrinkage target,in order to obtain the significance of parameter with multiple performance objectives.5)Based on the artificial neural networks,proposal and establish neural network,which mapped the relationship between these process parameters and warpage-shrinkage.Neural network is trained by the data,and supplemented 5 groups of data test model precision.