Based On The Digital Simulation Of Large Automotive Parts Injection Molding Process Optimization Design

Since automobiles are under the trend of being light-weighting, plastics are gradually used in the field. Their qualities of being light-weighting, anti-shock, and free design promote the significant development of automobiles. However, plastic materials in large mobiles tend to form sink marks due to their multi-rub structures and various size. Eventually, the shrinking of them will seriously affect the quality of the final products. During the forming process, the technological parameter has a direct influence on the floating status of the melt and the product of the final products. Getting assess to the optimized parameter is primary to the high-quality products.How to optimize the technological parameter in molding has been a great concern for the designers. Although CAE Analysis can imitate the molding process under certain technological conditions, its application is confined in the testament of the appropriateness of the technological devices. For those devices without obvious default, it’s hard to present the best technological plan. Therefore, it’s significant to establish the appropriate technological molds, optimize the molding process.The paper takes the greatest sink marks and the shrinking rate as indicators of good quality. It focuses on the molding imitation, effects of the technological parameter on the product quality, the optimization of technological parameter and the product quality. The paper tries to optimize the technological parameter by combining the optimization algorithm and the numerical modeling. Then the author carries out a molding experiment to testify the accuracy of the figures.The paper consists of five parts. Firstly, An appropriate mold was designed based on the modularization of the back inner-wall of the automobile. Secondly, a mold experiment with technological parameter was carried out in order to get analysis statistics for the initial products. Thirdly, analysis was given on the effects of the melt temperature, mold temperature, the filling and the pressure on the sink marks and shrinking rates. Eventually, a differential graph of technological parameter on quality was worked out, which could provide evidence for the optimization and control of it, as well as being a significant parameter as an indicator of the quality. Fourthly, the author worked out the nonlinear model with the application of Hybrid Genetic Algorithm. Finally, the accuracy of statistics were examine with the experiment using the inner car wall.