Abstract:The objective of this research is to find out the optimized process parameters for minimum shrinkage.For this purpose, the injection molded General Purpose Polystyrene (GPPS) part which is used in refrigerators is taken. The Taguchi method is used for design of experiments. For five parameters with three levels, L27 orthogonal array in case of Taguchi method is selected. The experiments are performed in Autodesk mold-flow insight simulation software with mold temperature, melt temperature, injection time, packing pressure and cooling time as process parameters. Analysis of variance is used to find out optimized set of process parameters and percentage effect of each parameter on shrinkage. Regression analysis is carried out to predict shrinkage value using regression equation. Artificial Neural Network (ANN) is used to predict shrinkage value for optimized process setting. Thus, experimental, statistical and computational approaches are used for validation of research.