IMPOS: A System Of Injection Molding Parameter Optimization And Simulation Based On GA

CAE techniques have, in recent years, become increasingly popular in plastic injection molding. For the advantages, such as prefiguring the filling process and optimizing the parameters, it has become the focus in injection molding field. However, in most practices, either molding parameters are not optimized or the optimization techniques are too complex to use. How to deal with this problem and design a feasible system still confuses the researchers. In this paper we discuss a fully automatic approach of integrated Injection Molding Parameter Optimization and Simulation (IMPOS) to plastic injection molding problems. In this method, a genetic algorithm is developed and integrated with an injection molding simulation system to achieve both parameter optimization and full automation of the process. The concept of evaluating the faults of injection molding is proposed. And the system is successfully developed in modular design method. Two experiments are taken to test the efficacy of the method.In this paper, we analyze the problems in most current studies, and then develop a system by using modular design method. The general content can be described as follows:First, the faults of injection molding are evaluated. There are many visible faults in plastic injection, such as insufficient filling, deformation, air bubbles and burn mark, etc. In order to using the faults as judgment of the optimization, they must be processed in mathematic method.Then select the parameters to construct the model. There are several factors influencing injection molding, such as material, the design of mold, process parameters, etc. The process parameters also include injection time, pressure, melt temperature, mold temperature, etc. In this paper, process parameters are selected to be optimized.The genetic algorithm (GA) is applied due to the characters of the model. Because the system model is complex and not formula, traditional optimization method can't deal with it. Also there are some advantages of GA, so it serves as the system's optimization algorithm.The system is developed in modular design method. And examples are taken to test it. Because of the advantages of modular design, the system and the method can apply to any plastic injection molding product.