Kistler Launches World First at Fakuma 2011: Automatic Online Prediction of Quality of Injection Molded Parts

This year's Fakuma sees Kistler showing a system for online prediction of the quality of injection molded parts. This new module for the CoMo Injection Type 2869B process monitoring system forecasts the quality of each component produced. Based on a process model and the measured process parameters, it provides online prediction, during actual molding, of parameters such as the final dimensions of the part. Immediately after molding it states whether dimensions will still be within tolerance when the part is used.

For the first time this allows direct monitoring of quality attributes, without the injection molder having to specify tolerance bands for process variables. Manufacturers of injection molded parts can now take tolerance bands straight from the parts specification as criteria for the CoMo Injection process monitoring system. Manufacturers of high-quality, hard-to-assemble or sensitive medical and other precision parts will profit most from this.

From Experimentation through Modeling to 100 % Quality
One important aspect of online quality analysis is modeling allowing sufficiently accurate calculation of the attributes of parts. The models are developed prior to production, for example in the mold trial phase.

Statistical design of experiments (DOE) is used on the basis of process know-how derived from both the known effect of machine settings on quality attributes and the machine operator's knowledge of the current production process. Mold cavity pressure and contact temperature are measured in subsequent tests. Parallel evaluation of the quality of the parts produced takes account of relevant constraints such as post-production shrinkage and recrystallization. Automatic analysis develops the process models by calculating the relationships between measurands and part attributes.

The models derived from this analysis are used for online quality prediction. They allow calculation of the relevant quality attributes in the production process, 100 % documentation of the quality achieved, reject separation and quasi real-time quality control.

As an option, online quality prediction is fully integrated into the widespread CoMo Injection Type 2869B... process monitoring system and the CoMo DataCenter Type 2829B database. This makes it part and parcel of automatic process monitoring yet user-friendly and highly responsive.

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