Application Of Numerical Optimization On Injection Molding Process Parameter Of Complicated Vehicle Exterior

Plastics industry has been a very important industry in national economy , and caused concerns among people , also gained prompt development. Because of the merit of itself, plastic has got more and more application in many fields,such as automobile, home appliance , instrument appearance , architectural decoration. Injection mould molding is very important in the whole plastics industry. In automobile industry,it has a trend that more and more automobile components are using plastic to replace the tradition metal material. CAE technology for plastic molding is very hot in current plastic processes industry, but there still exists series's problem.The thesis is according to the trend that more and more automobile components are using plastic and requires high quality. In this thesis, introduced the background and significance of researching injection molding process parameter of complicated vehicle exterior,the technology level of plastic componts home and abroad,the plastic trend of automobile components,the research and development of automobile exterior material home and abroad,analized the default of plastic injection parts and the reason ,the way to solve it,the development and application in injection molding of optimization method. Based to all,we know using numerical optimization method to analyze process parameters in injection molding has practical significance.In this thesis,using rear view mirror as the model,discussing how the process parameters affects the quality of the model when the material, injection machine , mould structure etc.,are certain. Warpage of the plastic will be set as the goal of the optimization. The injection temperatrure,mold surface temperature,injecting time, filling pressure,cooling time will be set as experiment genes. The value in the range of real project will be set as experiment levels. Injection process and warpage will be canied out in Moldflow. The data from numerical simulation will be arranged by Orthogonal Experiment. Then it will build mathematic model of injection moulding by regression analysis , BP neural networks and RBF neural networks,compare the effects of the three modles,and chose the best one. At last, the best modle is used as a Fit Function in the Genetic Algorithm (GA), with which can give the most appropriate parameter. Based to this thesis ,we can shorten the production time,improve the quality of the plastic part.