Prediction of sink depths using nonlinear modeling of injection molding variables

This paper deals with prediction of sink mark defects and its intensities on injection-molded thermoplastics components. A nonlinear mathematical model, in terms of injection molding variables, was developed using response surface methodology. Fractional factorial design (FFD) of experiments was used for initial screening of variables. Based on FFD, the four most influential and controllable injection molding variables were selected. Central composite design (CCD) of experiments was structured and conducted using flow simulation to formulate the predictive nonlinear model. Statistical analysis and experimental results suggest that the proposed model could be used for predicting sink mark depths with adequate accuracy. It indicates that this predictive model can be used for drawing tailor-made guidelines for designing as well as for processing. If it is applied at design stage, corrective and iterative design steps can be initiated and implemented for better quality of products without resorting to physical trials on molds. Proposed methodology can also be effectively employed in controlling the quality of products throughout the product life cycle.