Injection molding product weight: Online prediction and control based on a nonlinear principal component regression model

Weight is an important quality characteristic of injection‐molding products. The current work focuses on the online prediction and closed‐loop control of the product weight. Previous researchers used the process set‐points as the inputs to establish weight prediction model. These models cannot reflect the weight variations at a given setting. In this study, an online weight prediction model has been developed, with the process variable trajectories as the inputs, using a principal component regression (PCR) model. A nonlinear enhancement has been made to improve the prediction accuracy of the PCR weight model. Based on such an online prediction, a closed‐loop weight control system has been developed and tested experimentally. POLYM. ENG. SC. 46:540–548, 2006.