Extensive research has been conducted in an attempt to develop reliable models or indicators for determining product quality based on process information. Relationships between part quality and process variables such as nozzle temperature, hydraulic pressure and cavity pressure have been established using methods such as statistical process control, regression analysis and artificial neural networks. Ideally, these models would be used to determine part quality without direct inspection. If a level of confidence equivalent to that obtained by traditional methods (e.g., SQC) could be achieved, “quality by inspection” could be eliminated. Two drawbacks to these models are that they are specific to the machine/mold/polymer (M/M/P) combination being studied and they require a significant amount of “up-front” process data for model formulation. A method for “normalizing” pressure data obtained from a range of machine/mold/polymer configurations to yield essentially one curve or attribute denoting acceptable part quality would greatly enhance the utility of P-t data in a manufacturing setting. The objective of the present research is to examine the effects on the temporal cavity pressure due to changes in the mold geometry and to investigate methods for obtaining generic pressure data for various geometries. Cavity pressure data was collected using geometric inserts fitted into a standard ASTM tensile specimen cavity. The pressure data was analyzed to determine the correlation between cavity pressure and part quality for three part geometries studied. A discussion of the utility of the pressure is presented and an attempt is made to find a geometry independent cavity pressure attribute for use in determining part quality.

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