Inline quality prognosis of material condition induced process variations

Abstract

The main variation in a good quality production are induced by material condition. Processing technical polymers like PA, ABS or PBT possible influences are residual moisture conditions of the material or minor variations of raw material charges. Small changes in the material properties are difficult to detect at first quality controls and can be within the property tolerances. But even these small differences cause defects. The effects range from viscosity variations to varied crystalline properties. The influence of material properties on the processing have to be detected inline and combined with material analysis to a quality prognosis. The equipped sensors at injection molding machines enable an adequate process performance. The recently available solutions for power consumption monitoring enhance the available process control opportunities. Because of the high process speed of injection molding machines, the required sampling rate has to be minimal 500 Hz. A setup of high bandwidth data processing linked to the machine control enables precise characterization of the production. Identified index numbers, energetic data and characteristic development of measured process figures enable a high resolution detection of material induced variations. This prognosis enables inline classification of the produced parts and a compensation by correlating quality requirements with adjusted filling and packing parameters.