Multi-objective optimization of volume shrinkage and clamping force for plastic injection molding via sequential approximate optimization

Process parameters in plastic injection molding (PIM), such as the packing pressure, the mold temperature, the melt temperature, and so on, are generally determined by a trial-and error method through the experiments. Computer-aided engineering (CAE) in the PIM is an alternative approach to determine the optimal process parameters. In cap-type plastic product, large volume shrinkage makes the clamping difficult. Furthermore, small clamping force leads to high productivity as well as cost reduction. Both volume shrinkage and clamping force should then be minimized simultaneously, and a multi-objective design optimization is formulated. Inappropriate process parameters easily lead to short shot that the melt plastic is not fully filled into cavity. In this paper, short shot is handled as the design constraint. Numerical simulation of the PIM is so expensive that the response surface approach is valid. In particular, a sequential approximate optimization (SAO) that the response surface is repeatedly constructed and optimized with some new sampling points is recognized as one of the most powerful tools available. In this paper, the radial basis function (RBF) network is adopted for the SAO, and the pareto-frontier is identified with a small number of simulation runs. Numerical result shows that the pareto-frontier is well identified with a small number of simulation runs.