(58b) Predicting Process Performance in Screw Feeders Using Powder Flow Measurements
World Congress on Particle Technology
2018
8th World Congress on Particle Technology
Particle & Bulk Powder Characterization
Flow Properties of Particulate Solids II
Tuesday, April 24, 2018 - 1:45pm to 2:00pm
Automated, multi-variate powder characterisation tools provide reliable and comprehensive measurement of a powderâs response to process-relevant conditions. This data can then be correlated with process performance information to improve feeder efficiency and ensure high quality final products at the required rates.
Five powders were run through two different screw feeders, a DIWE-GLD-87 VR (a full flight single-screw feeder) and a DIWE-GZD (a flat-bottomed double-screw feeder) (Gericke AG, Switzerland). These materials were also tested using an FT4 Powder Rheometer® (Freeman Technology Ltd, UK) to evaluate their dynamic flow, bulk and shear properties. Multiple Linear Regression (MLR) analysis was then performed to evaluate the relationships between volumetric feed rate of the screw feeders and rheological properties of the powders.
MLR analysis demonstrated clear relationships between the GLD volumetric feed rate and two dynamic flow properties, Specific Energy (SE) and the Flow Rate Index (FRI). A correlation between GZD volumetric feed rate and Aerated Energy (AE) was also observed. The testing of two additional materials provided further support of these correlations and reinforced the models defined by the MLR analysis.
The two different screw feeders generate very different processing environments and therefore exhibited relationships with different rheological parameters. This emphasises the need for a multi-variate approach to powder characterisation.
This study shows the robust relationships that exist between powder flow properties and the volumetric flow rate delivered by different screw feeders and demonstrates how it is possible to generate a design and operating model that can be used to predict performance in order to optimise productivity.