AUTOMATED SELECTION OF GATE LOCATION BASED ON DESIRED QUALITY OF INJECTION-MOLDED PART

The objective is to develop a methodology that automatically predicts the ''optimal'' gate location(s) of injection molds based on injection -molding simulation. User-defined design evaluating criteria for three important parameters-warpage, weld and meld lines in a constrained ar ea, and Izod impact strength at the specific regions of the injection- molded part-are introduced to determine the optimal gate location. Amo ng the three parameters, the Izod impact strength is obtained using a previously trained neural network. The difficulty in predicting accura te values of engineering property like Izod impact strength is that th ey vary throughout a part with respect to the thermomechanical history . Upon evaluating each gate location, the trained neural network compu tation predicts, regardless of part geometry, Izod impact strength by a nonparameteric modeling of the complex relation with thermomechanica l processing histories. The methodology comprises a two-stage process: (1) choosing the best among a set of gate locations generated based o n a human designer's intuition, and (2) locally searching for the bett er gate location.