Melt temperature profile prediction for thermoplastic injection molding

A computer system is developed to quantitatively reveal how the melt temper ature is affected by the operating conditions during the plastication, dwel l and injection stages of the injection molding process. The variables cons idered in this study are rotation speed, back pressure, barrel heater tempe ratures, nozzle heater temperature, dwell time and injection velocity profi le. A set of Artificial Neural Networks (ANN) has been developed to predict the effect of the operating conditions on the melt temperature during plas tication. The dwell period is treated as a heat conduction problem. A free boundary model for the injection phase is developed to simulate the tempera ture development and melt flow due to the forward motivation of the screw. The overall prediction of nozzle melt temperature is in good agreement with the experimental measurement, validating the proposed procedure combining ANNs and mathematical modeling. This work enhances the understanding of the process and provides a basis for future work on the optimization and advan ced control of the process.