Instrumentation, analysis, and on-line simulation for improved process control of injection molding.

摘要

This research focuses on utilizing data from process sensors to determine the state of the polymer melt during the injection molding process. Both analytical approaches and numerical simulations are presented that are capable of estimating state variables such as melt temperature, specific volume, viscosity, and flow rate. Such variables can not be measured directly by conventional sensing techniques.; Data obtained from an IR temperature sensor and a pressure transducer located in the machine's nozzle were analyzed to quantify the behavior of the melt as a function of adiabatic compression, viscous dissipation, and varying screw recovery conditions. A method for calculating PVT relationships from process data is presented that shows correlation with published results. Observed melt temperature transients were found to depend most on the pressure, shear rate, and residence time.; A mold instrumented with an IR temperature sensor and an in-mold thermocouple was used to validate a method of predicting melt temperature from in-mold thermocouple data. The analysis consistently predicted the correct trend in the melt temperature although, it under predicted the magnitude of the melt temperature.; Improved process observability was then demonstrated via an on-line simulation, which dynamically controlled a molding machine based on the predicted melt state. The simulation was able to dynamically adjust the transfer position to eliminate flashing from a molding process that had not been optimized, but the simulation increased variability.