AN EXAMPLE n an example involving plastic compounding, engineers for the project had experience using a V-type rotating blender for similar materials at other plants. Batch ingredients would be fed into a scale hopper and then discharged into the blender. The blended batch would then be discharged into a surge bin feeding an extruder. While this process had worked successfully at other compounding plants, this plant would blend ingredients with a wider size range. The most extreme case involved blending the two materials shown in Figure 3, which consisted of cylindrical pellets with a nominal size of about 3 mm and nearly spherical beads with a size range from about 1mm down to 150 microns. Engineers for the project ran tests in a small-scale V-blender and evaluated blend uniformity by taking samples from the blender. The overall blend results showed a lot of scatter. Some samples were acceptable, while others were significantly outside the desired blend ratio. Engineers also noticed that when the batch was discharged after a test, the material in the receiving container was severely segregated. This prompted development of a more rigorous sampling method that included collecting samples from the discharge of the blender from beginning to end. When this was done the results, shown in Figure 4, clearly showed inadequate blending. Based on this realization, further testing was done to determine if a tumbling type of blender could be used. After a series of trials, a cylindrical blend vessel with an conical hopper and insert was found to produce a blend within specification, and discharge a blended stream to the downstream vessel. This example illustrates several key points about blending, segregation and sampling. First, the blender must provide the correct blending action for the solids. These two materials are very
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Sampling Sampling is essential in determining the state of the blend in a blender, in downstream equipment or in the final delivered product. Samples are analyzed to measure the variables of interest to the application, such as particle size, chemical composition, pH, dissolution rate, color and so on. The overall average of the sample results represents the average composition of the blend. Variations between samples provide a measure of 44
FIGURE 6. The sampling results for the new blender design show the improved performance. Area between dotted lines represents desired blend ratio
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property differences associated with size distribution, such as bulk density and fluidization behavior, but also differences in chemical composition. Fluidization segregation and particle entrainment. Other common mechanisms of segregation that act primarily on particle size are fluidization segregation and particle entrainment or dusting segregation. Fluidization segregation occurs where gas movement through a bed of solids causes finer, lighter particles to rise to the top surface of a fluidized blend of powder, while the larger, heavier particles concentrate at the bottom of the bed. Particle entrainment or dusting segregation occurs when fine particles in a blend are carried by air currents (such as during transfer of a blend into a container) and then settle preferentially at the container walls.
free flowing and hence blend easily. Blend time in the tumbling type blender is very short, on the order of tens of revolutions. However, the other side of the coin is equally important because the material also segregates readily, so maintaining the material in a blended state is difficult. This required two modifications to the geometry of the blend container. First, the dead zone near the center of the blender had to be reduced because the blender geometry did not allow enough diffusion to mix material in the center of the blender. Convection dominated the action in the blender, and diffusion occurred on the cascading surfaces, but some material remained poorly blended in the center. In addition to the blending performance, the flow pattern that developed during discharge had to be changed from funnel flow, where some of the blend remained stagnant during discharge, to mass flow, where all of the blend flowed as it discharged. In funnel flow, the highly segregating material could de-mix along shear surfaces during discharge. A mass flow pattern was achieved by designing a sufficiently steep hopper-shaped blend container with an internal bullet to displace material in the center of the container. The final configuration of the blender, shown in Figure 5, produced the results shown in Figure 6. The other important point illustrated in this example is sampling. Without sampling the blender discharge stream from start to finish, it would be impossible to know if the blend delivered to the extruder would be uniform and within specification. A blending process shouldn’t be considered as an independent step in a block diagram, but really must be treated as a synergy of the mixing activity, segregation and sampling to produce the desired end result. ❑
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blend uniformity. Variability can be expressed by statistical measures, such as standard deviation, coefficient of variation, or relative standard deviation, as well as other measures [2]. The single most important rule of sampling is to collect a sample that accurately represents the state of the blend at the point where it is sampled. In many industrial processes this is a significant challenge due to either the difficulty of getting a sample at the desired location or because of the potential for sampling error that is introduced by
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the sampling method. The two “golden rules” of sampling are to always collect a full stream sample, and always collect a sample while it is moving [3]. In the case of the cereal example given above, sampling is easy because the sample is either a whole box of cereal or individual servings poured from the box. In either case the sample is easy to get and it is possible to analyze the entire sample. For other processes, significant challenges can prevent the use of good sampling techniques. In an example involving limestone