Experimental-Based Multi-objective Optimization of Injection Molding Process Parameters

In this paper, the framework for determining the optimum injection molding process parameters for minimized product defects through experimental-based multi-objective optimization is presented. Two defects with regard to product quality, namely warpage and volumetric shrinkage, were examined. Seven injection molding process parameters are considered including the mold temperature, melt temperature, packing pressure, packing time, cooling time, injection speed and injection pressure. Specific test points determined, within a defined domain, using the face-centered central composite design approach were used to conduct actual injection molding experiments. Warpage and volumetric shrinkage were computed for the resulting injection-molded experimental products. Two relationships between the two defects and the process parameters, respectively, were constructed and formed the basis for the optimization. Using the two relationships, a multi-objective problem entailing minimization of the two defects was formulated and solved using the genetic algorithm. The results indicate a significant tradeoff between the warpage and the volumetric shrinkage. Assuming equal importance in minimizing both defects, additional experiments were conducted to validate the corresponding optimum. The experimental results revealed close agreements with the optimization results differing by about 7%.