Numerical Simulation Of The Injection Molding For Part And Warpage Control

With the consumers'higher requirements about portability and aesthetics of the electrical parts, the electric cover structure is getting more and more complex, while the requirements of appearance are also getting higher and higher. Nowadays, The company is very concerned about how to reduce Warping deformation of the cover and speed up its molding process.This subject comes from the cover research and development projects of Schneider-electric company. Firstly, This article introduces the developing situation of the numerical Simulation of the injection molding for part and warpage control. Then, the filling analysis, cooling analysis and packing analysis are performed by using Moldflow software. Secondly, to solve the warpage problem of the cover in the injection moulding process, the L27 orthogonal experiment table is designed and by Moldflow simulation, the effect factors of fixed mold temperature, movable mold temperature, melt temperature, rate of Screw, Screw position, packing time, packing pressure to influence the warpage of the cover are analyzed. The combination of process parameters to the smallest warping deformation is optimized. Then, by ANOM and ANOVA, the three factors which act the largest effect on Warp- ing deformation are obtained. There are fixed mold temperature, packing time and packing pressure. Based on this factors, by the complex method,the three important parameters (fixed mold temperature, packing time, packing pressure) are optimized to further reduce the amount of warpage of plastic parts. Through the research, the following conclusions are obtained: the smallest total warping deformation is 0.450mm by using orthogonal test, and using the complex method, the total warping deformation can be optimized to 0.432mm, 4% improved. So it follows that the complex method can further optimize parameters which is been set, and the effect is not significant. But it also demonstrated that on the base of the orthogonal test, other optimization methods can be used to optimize the orthogonal results furtherly, to shorten the actual tryout time.