Fault detection in a thermoplastic injection molding process using neural networks

Injection molding technology should assure a high level of quality control of the molded parts via automation. Inherent complexities of the process make mathematical modeling difficult, hindering the control quality demands of the conventional methods. Neural networks adaptive data based technology has been successfully applied in industrial applications as they rely on highly nonlinear models and are able to provide enough rich data for modelling the required process relationships. Neural networks are used herein for fault detection in the injection molding process. The next step is to develop a system for automatic tuning of machine setups.