Testing mixer performance

by Teresa Acklin
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The key to well-mixed feed is assuring optimal mixer operation.

   By Tim Herrman And Keith Behnke

   The objective of the mixing process is to produce feed in which nutrients and medication are uniformly distributed. Well-mixed feed enhances animal performance and is an essential step in complying with regulations in many countries.

   A satisfactory mixing process produces a uniform feed in a minimum time with a minimum cost of overhead, power and labor. Some variation between samples should be expected, but an ideal mixture would be one with minimal variation in composition. Measuring the variation in finished feed is the crux of mixer testing.

   A number of factors determines mixer performance and the dispersion of ingredients in a feed. Understanding how these factors affect the mixing process is essential when interpreting the results of a mixer test.

   Factors include ingredient particle size and shape, ingredient density and static charge, sequence of ingredient addition, amount of ingredients mixed, mixer design, mixing time, cleanliness of the mixer and wear or maintenance of the mixer. Feed manufacturers can control most of these variables through appropriate equipment maintenance and operation.

   Particle size of grain ingredients is controlled through the grinding operation. Coarsely ground grain (a large particle size) can have a detrimental effect on a batch of feed's mixing properties.

   For example, ground grain with a particle size of 1,200 to 1,500 microns reduces the likelihood of uniform incorporation of micro-ingredients compared with grain ground to an average particle size of 700 microns. A large particle size variation between grain and micro-ingredients also can result in increased segregation after mixing.

   The sequence of ingredient addition also determines ingredient dispersion in the mixing process. Mixers may have dead spots, where small amounts of ingredients may not be readily incorporated into the feed. This situation is aggravated when mixing ribbons, augers or paddles become worn.

   Ground grain or soybean meal should be the first ingredient added into a horizontal mixer. Vertical mixers generally provide an optimal mix when micro-ingredients are added early in the matching process.

   Buildup of material on ribbons, paddles or augers can reduce mixer performance. Regulations in some countries that pertain to production of medicated feed require equipment to be maintained and cleaned. Residual material on mixing parts can also lead to feed contamination (cross-contamination).

   Overfilling or under-filling a mixer can lead to inadequate mixing. Overfilling a horizontal mixer can inhibit the mixing action of ingredients at the top of the mixer. Conversely, filling a mixer below 50% of its rated capacity may reduce mixing action and is not recommended.

   The mixing time necessary to produce a homogenous distribution of feed ingredients should be measured for each mixer. Mixing time is a function of mixer design and the rotational speed of the ribbon, paddle or auger. The best way to establish the appropriate mix time is to conduct a mixer performance test.

Mixer Performance Testing.

   Mixer testing consists of two parts: sampling and sample analysis. Standard procedures exist for sampling mixers, analyzing samples and interpreting results.

   The first step in mixer testing involves collecting representative feed samples. This process depends on the type (horizontal or vertical) and design of the mixer. For example, it is difficult to collect a representative sample directly from a vertical mixer using a grain probe, so collecting samples at evenly spaced intervals during mixer discharge is recommended.

   Samples can be taken from the spout end of portable grinders/mixers or near the discharge point for a stationary vertical mixer. Horizontal mixers are usually accessible from the top, which permits sample collection directly from the mixer using a grain probe.

   Samples should be drawn from 10 predesignated locations, as shown in the accompanying diagram, or at even intervals during mixer discharge. Identify the location, or time sequence, by numbering the sampling bags; this step will help in interpreting the data.

   Ten samples are recommended, based on the statistical analysis procedures used to evaluate samples. Mixer test results are less accurate when fewer samples are used.

   If you are evaluating mixer performance using a micro-ingredient such as a drug that requires an expensive laboratory assay, it may be necessary to make a trade off between the cost and accuracy of the test.

   To select the optimum mixing time, feed samples must be collected at intervals over an extended period. For example, a horizontal mixer can be evaluated for optimal mixing time as follows: run the mixer for two minutes, stop the mixer and collect 10 representative samples from predetermined locations, run the mixer two more minutes, stop the mixer and collect 10 samples from the same locations as the previous sampling. Repeat this process for 10 minutes (five sampling times).

   As mentioned above, it is difficult to collect samples directly from vertical mixers. In this instance, a sampling scheme will involve separate batches of feed that have different mixing times. It is important to perform this test using the same feed ration and same sequence of ingredient addition to the mixer.

   Safety precautions must be followed when sampling a mixer. In every instance, use proper lockout, tag-out procedures (disengage power) before reaching into a mixer to collect a sample. Do not place your hands near moving augers when collecting samples during mixer discharge.

   Sample evaluation involves selecting the micro-ingredient or tracer to test for feed uniformity, assaying the samples for the specified ingredient level, analyzing and interpreting the data collected.

   The first step is selecting a micro-ingredient. A micro-ingredient is defined as an ingredient that makes up 0.5% or less of the final feed. Testing mixer performance using a micro-ingredient will provide a better indication of feed uniformity, since micro-ingredients are typically more difficult to incorporate into a large batch of feed.

   Salt is a commonly recommended micro-ingredient to test mixer performance. Salt is common in most feeds, it comes from only one source, and it is both inexpensive and easy to perform a salt assay.

   Physical characteristics that make salt an attractive ingredient for testing include the fact that it is more dense than most feed ingredients, its shape is generally cubic rather than spherical, and it is smaller than most other particles. If the mixer will uniformly incorporate salt, those ingredients with more typical physical properties of shape and density should pose no problem during mixing.

   Step two involves assaying procedures. Assaying samples for salt content may be performed using several techniques. The sodium or chloride ions from salt may be analyzed after mixing the feed sample in a water solution. Chloride titrators are used to measure the dissolved chloride, while a meter is used to measure the sodium. The titrators and meter both are available commercially.

   The third step in sample evaluation is analyzing the data. The average salt concentration (the mean) and the variation between samples (standard deviation) are calculated to arrive at a single value described as the coefficient of variation (CV). A desirable CV for a well-mixed feed, using the salt assay method, should be at or less than 10%. Table 1 contains the equation used to calculate the coefficient, but inexpensive calculators are available that are programmed with a statistical function to calculate the CV or the standard deviation and mean automatically.

   The last step in sample evaluation is interpreting the results. As seen in Table 2, a CV below 10% is considered a good mix. Variation in the assay procedure may be as high as 5% to 6%, indicating that the actual variation from mixing is about 5%.

   If the CV is more than 10%, increase the mix time and/or inspect the system for factors, such as particle size or sequence of ingredient addition, that caused the poor ingredient distribution.

   Tim Herrman is extension state leader, Department of Grain Science and Industry at Kansas State University, Manhattan, Kansas, U.S.; and Keith Behnke is a feed manufacturing specialist at Kansas State University.

Table 1

Calculating the coefficient of variation for salt distribution in feed is performed with the following equation:
%CV = s/y x 100
y = yi/n
s =/s2
s2 = (yi2)-ny2/n-1
%CV = percent coefficient of variation
s = standard deviation
s2 = variance
y = mean
yi = individual sample analysis results
n = total number of samples

Table 2

Interpreting mixer test results
Coefficient of variation in percent
RatingCorrective Action
< 10%ExcellentNone
10% to 15%GoodIncrease mixing time
by 25% to 30%
15% to 20%FairIncrease mixing time by 50%,
look for worn equipment,
overfilling or sequence
of ingredient addition.
>20%PoorPossible combination of all
of the above. Consult feed
equipment manufacturer.

How to evaluate mixer test results

   To illustrate the variation in salt concentration for a feed sample, consider the following example. Samples were taken from a horizontal paddle mixer with a 2-tonne capacity using a 1.2-meter grain probe. Titrators were used to measure the salt ion content with the following results:

Salt content
Location(in percent)
Standard deviation0.1156
Coefficient of variation22.10%

   Sampling scheme used to evaluate mixing performance in a horizontal paddle mixer.

   The sampling scheme that was followed is illustrated in the diagram. The lowest salt concentration was at location 1 and the highest was at location 9. Salt was added to the mixer as a premix after ground grain and soybean meal. The auger used to convey the premix discharged near the center of the mixer. Complete feed was discharged from the mixer end, where samples 9 and 10 were drawn.

   Results suggest that insufficient mixing action or time resulted in a low micro-ingredient distribution at one end of the mixer. Possible corrective action could include positioning the premix auger closer to sampling locations 1 and 2 (the end opposite to the mixer discharge port) or increasing mixing time to five minutes from three minutes.

   A particle size evaluation revealed that ground sorghum was 1,150 microns. Adjusting the roller mill to reduce particle size to fewer than 800 microns should improve mixer performance and feed efficiency in this example.