Based on the molding operator’s thought during the molding trial-runs

a hybrid intelligent model employing case-based reasoning

surrogate model and fuzzy inference was constructed. First

the idea of case-based reasoning was adopted for the initial process parameters setting

which simulated the molding operator’s behavior that one often recalls previous cases and sets the initial process parameters of the current one by referring to the previous ones. If the case-based reasoning failed to set the initial process parameters

a surrogate model was applied to determine the initial process parameters

which imitated a skilled operator’s “know-how” and intuitive sense acquired through long-term experience. Then

the molding trial would be run on the molding machine. Finally

a fuzzy inference based on expert knowledge was developed for correcting defects and optimizing process parameters during the molding trial run until the part quality was found satisfactory. A corresponding intelligent system was developed to be integrated with injection machine by communicating with the controller

and experimental studies showed that the intelligent system could be used in a shop-floor production environment.