Screw feeders are used in many industries to control the flow of powder into a process. The properties of the powder have a direct impact on feeder performance, making it essential to tailor the system to the product being handled. Poorly matched powder/feeder combinations can result in low feed rates, high screw torques and the accumulation of powder on the walls, all of which decrease short- and long-term operating efficiency.
Screw feeders consist of one or more rotating augers or helixes mounted in an enclosed chamber. As the auger rotates, powder is transferred according to the Archimedes screw principle. Three factors directly influence the specification of a feeder:
- Installation constraints associated with plant layout – the number of feeders, available headroom, feed distances and mounting requirements.
- Process requirements – feed capacity, operation mode (continuous or batch), operating pressure, required accuracy, and the extent of automation.
- Material properties – is the material free-flowing, cohesive, adhesive, fragile, prone to attrition, abrasive, compressible or fluidisable?
Key variables that can be manipulated to meet requirements include: the size of the feeder (diameter and length); the geometry, drive and pitch of the auger; and the accessories used to ensure consistent flow. Vibrational feeders and fluidisation/agitation in the feed hopper are all possible options. Feed rate may be controlled on the basis of weight (gravimetric) or volume (volumetric).
Specifying the optimal screw feeder for any given application is critical to operational success
Specifying the optimal screw feeder for any given application is critical to operational success. A feeder that is poorly matched to the product is likely to be associated with poor operation. For example, flow rate may be erratic or poorly controlled, directly affecting the overall performance and efficiency of the process. Alternatively, if the powder is cohesive, the accumulation of material within the equipment may be problematic, especially if there is frequent product changeover and sensitivity to batch-to-batch contamination.
Understanding how to characterise powders to predict performance in different equipment is therefore extremely helpful. Within a screw feeder, powders are subjected to different environments, flowing gravitationally from the feed hopper into the forcing, compacting flow regime within the rotating auger(s).
The way in which a powder responds to these conditions depends on its properties. In this study, experiments were carried out to assess whether properties measured using an FT4 Powder Rheometer correlated with feeder performance. The aim was to assess the feasibility of predicting feeder performance from powder properties to help identify an optimal screw feeder solution for any material.
Correlating powder properties with screw feeder performance: An experimental study was undertaken to identify correlations between the properties of the five powders detailed below and their performance in two different screw feeders.
- Calcium hydroxide
- Milk protein
- Calcium citrate
Samples of each powder were tested using the FT4 Powder Rheometer1. Dynamic, bulk and shear properties were measured with a high degree of repeatability (RSD<5%) in each case. Samples were then run through two different Gericke screw feeders to determine the volumetric flow rate (L/hr) delivered at an auger rotation speed equivalent to 80Hz. Volumetric flow rate (in L/hr) was calculated from measurements of mass flow rate (in kg/hr) and poured density.
The screw feeders used were a DIWE-GLD-87 VR, full flight single-screw feeder using tube No.3 and a DIWE-GZD flat bottom double-screw feeder using a 12 x 13.5mm tube with a conical core. The GLD machine is a compact, versatile feeder used for high accuracy feeding of dry solids in pilot scale applications and for those requiring frequent material changeover. The GZD unit is a compact, self-cleaning twin screw extruder used for low-capacity applications and is particularly suitable for materials with poor flow characteristics.
Table 1 shows the data set for all five powders. A multiple linear regression was performed to identify relationship in the data. This is a mathematical process that produces an equation quantifying a dependent (y) parameter in terms of influential, independent (x) variables. The process generates a ‘p’ value for each parameter, indicating the probability that the parameter’s contribution to the relationship is statistically insignificant. The higher the p value, the more likely that the parameter has no bearing on the relationship. A smaller p value is therefore associated with a more relevant parameter. For this study a p value of 0.1 was defined as the upper limit so parameters with higher p values were eliminated.
Table 1: Dynamic, bulk and shear properties for five powders alongside volumetric flow rate when run through the GLD screw feeder
For the GLD feeder, the multiple linear regression step produced the following relationship:
R2 is a measure of the ‘good fit’ between the model and the data. Values closer to unity indicate a good fit. This relationship suggests that only two dynamic properties are needed to robustly predict feeder performance – Specific Energy (SE) and Flow Rate Index (FRI). FRI describes how a powder’s resistance to flow changes as a function of flow rate. It is simulated by varying the speed of the helical blade.
Flow Energy is measured using a blade tip speed of 100, 70, 40 and 10mm/s. FRI is the ratio of the flow energy measured at 10mm/s to that measured at 100mm/s. An FRI greater than 1 indicates that the resistance to flow increases when the powder is forced to flow more slowly. All powders in this study generated an FRI >1, therefore exhibiting shear thinning behaviour.
Figure 2 shows the measured flow rates for the five powders along with the values predicted by the model. As suggested by the R2 value, the predicted values accurately describe the performance observed in the GLD feeder.
Figure 2: Predicted and actual feed rates for five powders in the GLD feeder
To confirm the predictive ability of the model, two additional powders were tested – cement and lactose. Figure 3 shows the measured flow rates for all seven materials, along with the values predicted from their properties. A revised R2 confirms close agreement between the predicted and measured flow rates for all seven materials, demonstrating the feasibility of predicting volumetric flow rate from powder properties.
Figure 3: Predicted and actual feed rates for seven powders in the GLD feeder, illustrating the ability of the model to predict volumetric flow rate
The same process was repeated to derive a model for predicting performance in the GZD feeder (see data in Table 2).
Table 2: Dynamic, bulk and shear properties for five powders alongside volumetric flow rate when run through the GZD screw feeder
A simpler correlation was observed with Aerated Energy (AE), found to be a highly relevant parameter.
AE is the flow energy of the material measured when the sample is aerated by air flowing through it at a defined velocity, in this case 40mm/s (AE40). Cohesive powders tend to have a relatively high AE, since aeration does not significantly alter their resistance to flow. Free-flowing powders can generate AE values close to zero as they fluidise. The materials tested here exhibit a broad range of AE values, but the relationship between AE and volumetric flow rate remains robust.
Figure 4 shows the measured flow rates for the five powders along with the values predicted by the derived model. As suggested by the R2 value, the predicted values again accurately describe the performance in the GZD feeder. This study was also extended to verify the ability of the model to predict the flow rates for cement and lactose. As before, the correlation remained robust in this predictive mode (see Figure 4).
Figure 4: Predicted and actual feed rates for seven powders in the GLZ feeder, illustrating the ability of the model to predict volumetric flow rate
The results from this study demonstrate the ability to develop strong correlations between powder properties and volumetric flow rates in different screw feeders. Each feeder imposes different conditions on the powder which is reflected in the attributes of the powder that are found to be relevant for predicting performance. However, in both cases it was dynamic properties that were found to be most relevant.
This approach can be applied to determine correlations for predicting performance in a wide range of processing equipment. Multi-faceted powder characterisation provides an essential foundation by identifying properties that are relevant to performance in any unit operation. Thus powder testers that enable this approach can be valuable for process optimisation.
How the FT4 Powder Rheometer works
The FT4 Powder Rheometer enables bulk, shear and dynamic flow properties to be measured, providing a multi-faceted approach to powder testing that can be used in identifying properties that dictate process performance.
Dynamic powder testing was developed in response to the need to measure powder flowability under conditions that closely represent the process environment. Dynamic properties are determined by measuring the torque and force acting on a helical blade as it rotates through a powder sample along a defined path (see illustration). It therefore has an easily comprehensible measurement principle that can be intuitively related to flow behaviour in many unit operations, such as screw feeding.
Basic Flowability Energy (BFE) is measured on the downward traverse of the blade and reflects how powders flow under forcing conditions in confined states. In contrast, Specific Energy (SE) is measured as the blade travels upwards imposing a gentle lifting action on the powder. This parameter closely reflects behaviour in low stress, unconfined environments.
A range of other dynamic properties can be evaluated by extending these protocols to investigate powder performance in process-relevant ways. Dynamic test methodologies are well-defined, automated, and incorporate sample conditioning to ensure that powders are tested in a reproducible state. Dynamic testing can often differentiate powders that other techniques suggest are identical.
This approach, combined with a unique capability to measure powders in consolidated, conditioned, aerated or even fluidised states, makes dynamic testing a powerful technique for process-related studies.
FT4 Powder Rheometer is a registered name of Freeman Technology
1. Freeman R. 'Measuring the flow properties of consolidated, conditioned and aerated powders — A comparative study using a powder rheometer and a rotational shear cell', Powder Technology 174 (2007) 25–33.
Jamie Clayton, Operations Director, Freeman Technology
Doug Millington-Smith, Applications Specialist, Freeman Technology
Ralf Weinekötter, Managing Director, Gericke AG (www.gericke.net)