Optimization Of The Injection Molding Simulation And Process Parameters Based On Artificial Neural Network

The development of plastic products trends to the functionalization, intelligentization and subdivision with the diversity of plastic product applications. Injection molding is a subject containing processes of the complicated physical and chemical changes. Study of the computer simulation and emulate and the optimization of technical parameters of injection molding improves quality and yields of plastic products, reduces the cost and increases profit, so it is of great instructive significance to production.For the purpose of the optimization of process parameters of injection molding, in this paper, a3D model of product was built by using PRO-E and with the CAE technique, and further was imported to Moldflow. Then, the simulation and emulates were done depending on the machine and the supporting environment. The relative experiment was done by the introduction of the relevant raw material and process parameters. Using the signal-to-noise ratio analysis and orthogonal test and the mathematical statistical method such as the average analysis, mean analysis, variance analysis, and artificial neural networks and MATLAB, the optimized process parameters were obtained.The major studies and results are as follows:1. The technical theory and development of injection molding, such as the defects of the products during injection molding, were introduced in brief. The optimization of technical parameters of injection molding was studied by takeing the filling time, mold temperature, melt temperature, dwell pressure, dwell time and cooling time as independent variables and the warpage deformation and cubical contraction as induced variables.2. In this paper, combining a mathematical model of viscosity of injection molding, the mathematical theory of the filling, dwelling and cooling processes of injection molding were discussed, at the same time, analysised the effects of the three process on the product quality..3. The relevant gating and cooling systems were built by using CAE and Moldflow, and computer model of injection molding, which provided basic model to study injection molding parameters and simulation, was obtained in this paper.4. Makes use of Taguchi DOE(design of experiment), works out the optimized group by means of average analysis, works out the variation tendency of plastic through experiment factors and its influence degree by means of mean analysis;and works out the percentage of various experiment factors’ influence degree by means of variance analysis.5. BP network system based on MATLAB was designed and ANN model was built by using the artificial neural networks with the ability of high nonlinear mapping. The quality control of products was realized by the prediction of warpage deformation and cubical contraction of the plastic products.6. The relevant optimized group was obtained by using fine analytical method, and both of the deformation and the ratio of bulk shrinkage were further optimized.