A robust optimization of injection molding runner balancing

Abstract

A general methodology to robust process optimization that incorporated several innovative strategies was developed and applied to the injection molding runner balancing problem. The variables were systematically perturbed according to a design matrix to simulate the effects of process variation, which were characterized by the extent that rejected parts violated the predefined tolerances. The runner balancing optimization problems were characterized by multiple objectives and constraints, which consider cost, product quality and sensitivity to process variation. The resulting problems were solved by optimizing the independent variables with a multi-objective genetic algorithm. For optimizations that varied the runner diameters, several robust solutions were identified which required larger runner system volumes, but were significantly less sensitive to the effects of process variation when compared to deterministic solutions. The key parameter was the diameter ratio between the secondary runners furthest from the injection point. Optimizations that varied the runner lengths in addition to their diameters significantly reduced the volume needed to balance a robust runner system, when compared to the results of optimizations that only varied the runner diameters.