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 area, and Izod impact strength at the specific regions of the injection-molded part-are introduced to determine the optimal gate location. Among the three parameters, the Izod impact strength is obtained using a previously trained neural network. The difficulty in predicting accurate values of engineering property like Izod impact strength is that they vary throughout a part with respect to the thermomechanical history. Upon evaluating each gate location, the trained neural network computation predicts, regardless of part geometry, Izod impact strength by a nonparameteric modeling of the complex relation with thermomechanical processing histories. The methodology comprises a two-stage process: (1) choosing the best among a set of gate locations generated based on a human designer's intuition, and (2) locally searching for the better gate location.