Powder Processing and Predicting Feeder Performance

An important goal of the powder processing industries is to predict the performance of processing equipment from measurements of powder properties.

This article, presents a new collaborative study from Freeman Technology and Gericke to establish predictive correlations for the volumetric flow rate delivered by screw feeders, using dynamic powder testing, which can be used to accelerate and optimize screw feeder selection.

Screw feeders are used on a regular basis in the powder handling industries to control the flow of material from a hopper into a process. The performance of the feeder is directly influenced by the properties of the powder, making it necessary to tailor the design of any given system to the product being handled.

Generally, a poorly matched feeder/powder combination will be associated with high screw torques, low feed rates, and the accumulation of powder on the tube walls. Both short and long term operating efficiency is decreased by these factors.

This article describes collaborative research conducted by Freeman Technology (Tewkesbury, UK) and Gericke (Zurich, Switzerland) to identify powder properties that can be reliably measured to predict feeder performance.

The study highlights the value of dynamic powder characterization within this context, concluding that the development of robust models enable the prediction of the feed rate through a screw feeder from flow properties such as aerated energy (AE), flow rate index (FRI), and specific energy (SE). These models make the selection of a feeder for a specific powder easier, predicting its likely performance with a high degree of confidence.

Specifying Screw Feeders

Screw feeders are equipped with one or more rotating augers or helixes that are mounted in an enclosed chamber (Figure 1). As the auger rotates, powder is transferred according to the Archimedes screw principle, which has been manipulated for material transport for centuries.

A screw feeder transfers powder using one of more augers enclosed in a tube

Figure 1. A screw feeder transfers powder using one of more augers enclosed in a tube

Various industries use screw feeders, and Gericke has been routinely supplying machines for handling foods, chemicals, construction minerals, detergents, and plastics for several decades. Three factors directly influence the choice and specification of each feeder. They are:

  • Installation constraints associated with the plant layout – the number of feeders, feed distances, available headroom, and mounting requirements
  • Material properties – is the material being handled free-flowing, adhesive pr cohesive, fragile and prone to attrition, abrasive, fluidisable or compressible
  • Process requirements – feed capacity, whether the plant is operating continuously or in batch mode, the accuracy required, operating pressure, and the extent of automation

The size of the feeder (length and diameter), the drive, geometry and pitch of the auger, and the accessories used to ensure consistent flow are the main design variables that can be manipulated to meet any combination of requirements.Vibrational feeders and fluidisation or agitation in the feed hopper are all possible options. Feed rate may be controlled on the basis of volume (volumetric or weight (gravimetric).

Specifying the optimal screw feeder for any given application is critical to operational success for Gericke. Any feeder that is not properly matched to the product it is handling is likely to be associated with poor long term operation, which can manifest in many ways.

For example, flow rate may be erratic or poorly controlled, which could directly impact the overall efficiency and performance of the process. However, if the powder is cohesive, material accumulation within the equipment may be problematic, particularly if there is frequent product changeover and/or sensitivity to batch-to-batch contamination.

Therefore, understanding how to characterize powders helps to predict their performance in different types of equipment. Powders are subjected to different environments inside the screw feeder, flowing gravitationally from the feed hopper into the forcing and potentially compacting flow regime inside the rotating auger(s) that drives the material forward.

The properties of the powder directly determine the way in which a powder responds to these conditions. Consequently, powder properties have a major impact on the choice of equipment and the need or otherwise for bespoke development.

Collaborative research between Gericke and Freeman Technology assessed whether properties measured using the FT4 Powder Rheometer® could be correlated directly with feeder performance. The main aim of the study was to assess the feasibility of predicting feeder performance from powder properties to speed up the identification of an optimal screw feeder solution for any given material.

Correlating Powder Properties with Screw Feeder Performance

To investigate correlations between the properties of five different powders and their performance in two different screw feeders, an experimental study was conducted. The following powders were tested:

  • Maltodextrin
  • Calcium Hydroxide
  • Milk Protein
  • Calcium Citrate
  • Cellulose

In the first stage of the study the FT4 Powder Rheometer1 was used to conduct comprehensive testing of each powder sample. In each case, bulk, dynamic, and shear properties were measured for each powder with a high degree of repeatability (RSD<5%).

Please click here if you would like more information on the instrument used in this article or a quote

To determine the volumetric flow rate (L/hr) delivered at an auger rotation speed equivalent to 80 Hz, samples of each powder were run through each of two Gericke screw feeders. Using measurements of poured density and mass flow rate (in kg/hr), volumetric flow rate (in L/hr) was calculated.

The two screw feeders used were a DIWE-GZD flat bottom double-screw feeder using a 12 x 13.5 mm tube with a conical core and a DIWE-GLD-87 VR, full flight single-screw feeder using tube No. 3.

The GZD unit is a compact, self-cleaning twin screw extruder that is used for low capacity applications, particularly those suitable for feeding materials with poor flow characteristics. The GLD machine is a versatile, compact feeder that is used for high accuracy feeding of most dry solids, for applications that require frequent material changeover and those in pilot scale.

The data set measured for all five powders, including the average volumetric feed rate in L/hr, is shown in Table 1. To reveal correlations between these two sets of data a multiple linear regression was performed. This is a mathematical process that produces an equation to quantify a dependent (y) parameter (volumetric flow rate, in this case) in terms of influential independent (x) variables (the powder properties, in this case).

In this process, a p value is generated for each parameter, which indicates the probability that the contribution of the parameter to the relationship is statistically insignificant.

The higher the p value, the more likely that the parameter has no bearing on the relationship. Hence, a smaller p value is associated with a more relevant parameter. In this study, a p value of 0.1 was taken as the upper limit for relevance, and parameters with p values higher than this were eliminated to derive a robust relationship.

GLD Feeder

Table 1. Dynamic, bulk and shear powder properties for five different powders alongside the volumetric flow rate each delivered when run through a GLD screw feeder

Dynamic Parameters Bulk Parameters Shear Parameters Feeder Parameters
Material BFE mJ SE mJ/g SI FRI AE40 mJ AR40 NAS s/mm CE50tap g/mL BD50tap g/mL CBD g/mL CPS % [email protected] kPa mbar [email protected] kPa mbar UYS kPa MPS kPa FF Cohesion kPa AIF o WFA o GLD L/hr
Calcium Hydroxide 354 6.92 1.30 2.40 65 4.1 0.417 460 0.538 0.499 25.2 14.87 65.3 5.89 18.21 3.09 1.525 35.2 30.8 185.2
Maltodextrin 1282 5.19 1.11 1.16 13 107.3 0.156 1341 0.608 0.557 7.1 0.51 0.54 0.88 16.42 18.57 0.221 36.9 27.4 138.9
Milk Protein 330 8.49 0.91 1.37 102 3.3 0.182 613 0.311 0.267 24.3 3.07 9.06 3.96 20.71 5.23 1.091 32.3 24.6 128.7
Cellulose 630 8.92 0.87 1.34 19 46.0 0.619 4124 0.376 0.327 22.2 2.75 3.97 6.68 22.06 3.30 1.579 39.4 17.5 115.8
Calcium Citrate 680 12.50 1.07 1.40 225 3.0 0.077 914 0.261 0.234 41.6 1.02 37.82 8.14 22.59 2.78 1.877 40.5 41.0 50.13

GZD Feeder

Table 2. Dynamic, bulk and shear powder properties for five different powders alongside the volumetric flow rate each delivered when run through a GZD screw feeder

Dynamic Parameters Bulk Parameters Shear Parameters Feeder Parameters
Material BFE mJ SE mJ/g SI FRI AE40 mJ AR40 NAS s/mm CE50tap g/mL BD50tap g/mL CBD g/mL CPS % [email protected] kPa mbar [email protected] kPa mbar UYS kPa MPS kPa FF Cohesion kPa AIF o WFA o GZD L/hr
Calcium Hydroxide 630 8.92 0.87 1.34 19 46.0 0.619 4124 0.376 0.327 22.2 2.75 3.97 6.68 22.06 3.30 1.579 39.4 17.5 34.98
Maltodextrin 354 6.92 1.30 2.40 65 4.1 0.417 460 0.538 0.499 25.2 14.87 65.30 5.89 18.21 3.09 1.525 35.2 30.8 33.02
Milk Protein 1282 5.19 1.11 1.16 13 107.3 0.156 1341 0.608 0.557 7.1 0.51 0.54 0.88 16.42 18.57 0.221 36.9 27.4 29.88
Cellulose 330 8.49 0.91 1.37 102 3.3 0.182 613 0.311 0.267 24.3 3.07 9.06 3.96 20.71 5.23 1.091 32.3 24.6 18.67
Calcium Citrate 680 12.50 1.07 1.40 225 3.0 0.077 914 0.261 0.234 41.6 1.02 37.82 8.14 22.59 2.78 1.877 40.5 41.0 10.39

This multiple linear regression step produced the following relationship for the GLD feeder:

Feed Rate = 49.54 FRI – 13.81 SE + 163.8
(R2 = 0.9466)

R2 is a measure of the ‘goodness of fit’ between the model and the data with higher values closer to the upper limit of 1, indicating a close fit. This relationship suggests that only two dynamic properties – flow rate index (FRI) and specific energy (SE) – out of all of the properties measured are required to robustly predict feeder performance.

While SE reflects how a powder behaves when in an unconfined state, FRI describes how the powder’s resistance to flow changes as a function of flow rate, and is simulated by decreasing or increasing the tip speed of the helical blade of the powder tester.

Flow energy is measured at a blade tip speed of 100 mm/s (as for BFE testing) and then at 70, 40 and 10 mm/s during FRI testing. The FRI value is the ratio of the flow energy measured at 10 mm/s to that measured at 100 mm/s. An FRI above 1 indicates that the resistance to flow is greater, as shown by higher flow energy, when the powder is made to flow more slowly.

All the powders measured in this study have an FRI greater than 1 and hence exhibit this shear thinning behavior.

The measured flow rates for the five powders and the values predicted by the derived model are shown in Figure 2. As suggested by the R2 value for the coreelation, the predicted values accurately describe the observed performance of the powders in the GLD feeder.

Predicted vs. actual feed rate data for five powders, showing the close relationship between values predicted from the GLD model using measured dynamic powder properties and those measured in the experiments.

Figure 2. Predicted vs. actual feed rate data for five powders, showing the close relationship between values predicted from the GLD model using measured dynamic powder properties and those measured in the experiments.

Two additional powders – lactose and cement – were tested to challenge the predictive ability of the derived relationship. The measured flow rates for each of the original five powders, the two new materials (red), and the values predicted from their powder properties are shown in Figure 3.

A revised R2 confirms close agreement between the measured and predicted flow rates for the data sets incorporating all seven materials, and the viability of predicting volumetric flow rate from powder property data.

Predicted vs. actual feed rate data for seven powders illustrate the ability of the derived model to predict volumetric flow rate through the GLD feeder, from measurements of dynamic powder properties.

Figure 3. Predicted vs. actual feed rate data for seven powders illustrate the ability of the derived model to predict volumetric flow rate through the GLD feeder, from measurements of dynamic powder properties.

The same process was performed again to derive a correlation that could be used to predict performance in the GZD feeder. A simpler correlation was observed with Aerated Energy (AE), the only parameter found to be highly relevant.

Feed Rate = -0.1114 AE40 + 34.82
(R2 = 0.8383)

AE is the flow energy of the material measured when the sample is aerated by air flowing up through it at a defined linear velocity. In this case the defined linear velocity is 40 mm/s and therefore, the AE is AE40.

Cohesive powders tend to have a relativelt high AW since aeration does little to reduce the resistance they present to flow, while for free-flowing powders AE can approach 0 as the powders fluidise. The materials tested exhibit a relatively broad range of AE values, but a robust relationship between AE and volumetric flow rate holds for all materials.

The measured flow rates for the five powders and the values predicted by the derived model are shown in Figure 4. The predicted values accurately describe the true performance of the powders in the GZD feeder, as suggested by the R2 value for the correlation.

The study was extended to verify the ability of the relationship to predict the volumetric flow rate achieved with lactose and cement, as it was with the other feeder. As in the previous case, the correlation performed robustly in this predictive mode (Figure 4).

Predicted vs. actual feed rate data for seven powders illustrate the ability of the derived model to predict volumetric flow rate through the GZD feeder from measurements of dynamic powder properties.

Figure 4. Predicted vs. actual feed rate data for seven powders illustrate the ability of the derived model to predict volumetric flow rate through the GZD feeder from measurements of dynamic powder properties.

Predicting Performance

The results of this research show the feasibility of developing robust correlations between the volumetric flow rate delivered by different designs of screw feeder and measurable powder properties.

Different process conditions are imposed on the powder by each screw feeder. This is reflected by the powder’s specific attributes and the parameters found to be relevant for predicting feeder performance. However, instead of the bulk or shear properties, it is the dynamic powder properties that were most relevant in both cases.

The approach adopted in this study can be applied to determine the correlations to predict the performance of a variety of powder processing equipment. Multi-faceted powders provides the foundation for such work, and supports the identification of those properties that are most relevant to the performance of a powder in any specific unit operation. Therefore, powder testers that enable this approach can be highly valuable for optimizing a wide range of powder processes.

References:

  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.

This information has been sourced, reviewed and adapted from materials provided by Freeman Technology.

For more information on this source, please visit Freeman Technology.

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