Optimization Study On Gating System And Molding Process Parameters Of Injection Molding

Injection molding is one of the most common plastics processing methods in thecurrent. With the wide use of injection products in the high-tech field of home appliancesand automobiles, the quality, performance, and product upgrading of the plastic parts areproposed on a higher demand. Warpage is one of the most important factors affecting thequality of plastic product, which not only seriously affect the appearance quality of plasticproduct, but also affect the assembly quality of product, and even cause the productscrapped. It can improve the warpage of plastic product to guarantee the quality of theplastic product. The improvement of warpage can be achieved by optimizing the gatingsystem and molding process parameters. Therefore, the optimization of gating system andmolding process parameters has practical value in engineering.This paper, plate parts, for example. Based on considerable quantities experiment dataand numerical simulation methods. Used Moldflow, Orthogonal Experiment Method andArtificial Neural Network, aimed to research on the improvement of the warpage of plasticproduct.First, according to structure size of plate part and the principle of establishing gatingsystem, two different gating systems of plate part are established. Moldflow is used to doanalysis on different molding schemes with different gating systems. Comparing withquality indicators of the flow and warpage of the different molding program, the gatingsystem of the plate part is optimized.Second, molding process parameters which affect the warpage of plastic product arestudied. Which are selected is tested in accordance with Orthogonal Experiment.According to the Orthogonal Experiment Method and Variance Analysis, the moldingprocess parameters are established, which include melt temperature(MeT), packingpressure(PP), packing time(PT) and glass fiber content(GF%). Base on OrthogonalExperiment Method, full combination experiments of four factors with four levels are arranged, each molding process parameters affected on warpage is described. The resultstell us that the warpage of plastic product is reducing with the increasing of MeT, but withthe continuously increasing of MeT, the warpage of plastic product is almost unchanged,there is even a tendency to increase. With the increasing of PP, PT, GF%, warpage ofplastic product is reducing.Finally, base on full combination experiment data, the corresponding BP artificialneural network model is established to describe the relationship between injection moldingprocess parameters and the warpage of plastic product, and the reliability and correctnessof the BP neural network model is verified. The predicting capability of BP neural networkis used to predict the warpage of plate part in other different molding process parameters,the affection on warpage caused by single molding process parameters and interaction ofdifferent molding process parameters is described. The predicting results tell us that thewarpage of plastic product is reducing with the increasing of MeT, when MeT reaches230°C, with the increasing of MeT, the warpage of plastic parts is almost unchanged, there iseven a tendency to increase. With the increasing of PP, PT, GF%, the warpage of plasticproduct is reducing. The warpage of plastic product caused by interaction of differentmolding process parameters is significant.This study shows that the optimization of gating system and molding processparameters effectively reduce the warpage of plate parts. The combination of injectionmolding technology and numerical simulation can not only improve the quality of theplastic product, but also improve the efficiency of the product.