Research on Injection Molding Simulation and Process Parameter Optimization of Automobile Front Door Sill Press Plate

Abstract With the continuous development of plastic strip steel technology, optimization of plastic part process parameters has become one of the hot research in the field of injection molding. This paper takes the automobile front door sill pressure plate as the research object, analysis of optimal gate position and design of three pouring systems by Moldflow, evaluation of each index of the three pouring systems using the integrated scoring method, determines the optimal gating system. Five parameters such as mold temperature and melt temperature were selected as experimental factors, volume shrinkage and warpage are used as evaluation indicators, design and completion of signal-to-noise ratio-based orthogonal tests, determining the optimal combination of process parameters using grey correlation analysis, the results showed that the volume shrinkage and warpage deformation of the two evaluation indexes were reduced by 22.27% and 20.82%, respectively, after optimization. The set of Pareto solutions for volume shrinkage and warping deformation is then obtained by building an Ellipsoidal Basis Function Neural Network (EBFNN) model combined with a Non-dominated Sorting Genetic Algorithm (NSGA-II), and the relatively optimal five sets of Pareto solutions are selected for analysis and comparison, the optimum process parameters were determined as mold temperature 40.5°C, melt temperature 221.4°C, injection time 3.9s, packing pressure 54.8 MPa and packing time 39.s, the maximum volume shrinkage of the optimized part is 5.475%, the warpage deformation is 1.010mm, and the forming quality of the part is improved.