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Optimizing mixing performance through filler dispersion control.

The fact that good dispersion is important for the mechanical properties of a rubber compound is indisputable. Dispersion has, in numerous investigations, been shown to correlate to physical properties like tensile strength (refs. 1-6), modulus of elasticity (refs. 7 and 8), tire treadwear (refs. 9 and 10) and dynamic properties (refs. 2, 3 and 11-18).

Recently, with the increasing requirements for reliable processing in the competitive rubber industry, the focus has moved towards the use of dispersion test results to better predict the processing properties of the rubber compound. The aim of this article is to describe a tool for improved mixing and manufacturing economy. The presence of agglomerates with a diameter larger than 40-50 [micro]m may cause detrimental surface defects in manufacturing on a broad scale, ranging from surface flaws to severe processing problems in extrusion. The correlation between dispersion data, the general processing performance in general (refs. 12 and 18) and the rheological properties in particular (refs. 5, 19 and 20) are also reported in the literature.

Dispersion test instrument development.

The development of instruments for managing industrial processes, regardless of type, usually passes through three phases:

* Initial laboratory trials;

* a second phase in which the results from continuous and systematic measurements are used to manually adjust manufacturing steps or processes; and

* a final step in which earlier experiences are transformed into algorithms used interactively in an overall managing information system together with the production equipment.

Reliable dispersion testing is particularly important for new rubber materials containing new filler combinations. In such cases there is a need for accurate characterization to speed up test programs by limiting the number of necessary test runs. During years of tests on tires in different environments and testing conditions, matrix methods have been found to work well in predicting the wear resistance of tires. The need for well dispersed rubber has also become more evident for larger manufacturers of other rubber components besides tires, since the performance and processing limits are continuously stretched. This need for fast and reliable testing has generated a number of different types of equipment for optimizing the manufacture of rubber goods. Dispersion test equipment expected to fulfill the requirements indicated may be based on one or a combination of the following: Electrical methods (refs. 11 and 22);

* mechanical methods (refs. 23 and 24);

* transmission- and scanning electron microscopic methods (refs. 25-27);

* spectroscopic methods (refs. 25, 28 and 29); and

* optical dispersion test methods (refs. 4, 22, 27 and 30-34).

Among the known dispersion test methods, the latter has attracted a special interest and is more widely used. This is probably due to its close relation with the most common practical way of judging a rubber mix or vulcanizate, to cut a piece of it and simply look at its cross section. It is a quick test for an experienced rubber technician, and requires hardly any technical equipment. Even small differences in the topography of a surface are recognized without magnification. The features found to be of interest are difficult to describe and characterize in a mathematical way, it is simply a complex judgement based on pattern recognition by a skilled observer.

The next step in improving the evaluation of the dispersion level is to use a method other than the naked eye. Observing the magnified surface might better distinguish and highlight parts which are characteristic for a certain combination of rubber and filler. A microscope with a camera at a fixed angle of light and fixed magnification (ref. 35) made it possible to evaluate and record the test piece under controlled conditions. It also made direct comparison possible with earlier evaluations, e.g., in house corporate standard pictures.

A large step towards a practical test was taken by Persson, whose pioneering work resulted in the invention of the Split-Field evaluation (ref. 36). His apparatus, figures 1 and 2, utilizing a video or CCD imaging camera, enables direct comparison between an unknown freshly cut surface and images of cut surfaces representing international or corporate standards which, in turn, represent known variations in dispersion. In this way, immediate and direct comparison is made between the sample surface and the reference picture. The idea has been adopted as an ISO-standard test method (ref. 34).


The final step in the instrumentation evolution involves transformation into an "operator independent" state which strives to reduce parameters linked to the actions of an operator that might affect the test result. In dispersion measurements utilizing optical test methods, the difficult part is to characterize the test surface. Haralick (ref. 37) claimed that all pictures or images consist of three components to a greater or lesser extent: Spectral, textural and contextural features. The spectral features describe the differences in the grey-scale, textural features contain information on how parts with different grey levels are distributed on the surface (plane), and con-textural features contain information derived from blocks of discrete data surrounding the area being analyzed. The spectral and (textural) spatial parts were regarded as the most important in describing the surface mathematically.

Several units of test equipment aimed at automatically describing the dispersion level exist today (refs. 4, 24, 38 and 39). Also in this case, optical instruments are in the majority.

We believe that the minimum requirements on a test instrument for automatic classification of filler dispersion are:

* Reproducibility in manufacturing. In order to secure maintenance and compatibility between instrument versions, there must be a continuity in the development done in close cooperation with the instrument manufacturing procedures. It is essential that new versions of the instrument are compatible with earlier versions regarding test results. Therefore, only components which perform according to initially specified functional requirements can be allowed. This will not only reduce maintenance costs, but also the variability in the manufacturing steps which will automatically increase system performance and accuracy.

* A standardized calibration procedure. The approved level of the test result must be related to some definite standard or standard procedure that easily can be reproduced. In order to independently compare test results, there must be a mutual agreement among the users of a certain test method. The calibration procedure must correct unavoidable deterioration of the optical system due to, e.g., contamination and decrease in illumination, and be fast and simple in order to be performed as intended.

* Repeatability. The measured values must be repeatable so that significant effects are distinguished from effects depending on pure chance. This calls for a method with the lowest possible noise.

* Reproducibility. It must be possible to reproduce the test independently of time, test site, personnel, etc., by following the specified conditions and procedures, as described in the instructions for testing according to the test method.

* Representative sampling area. An optimal test area should be used. The test surface must be large enough to allow the algorithm to process an image that contains enough statistical information for correct processing. The measuring range of the instrument must cover the dispersion levels that are expected for a certain material group at a definite instrument setting, and the same evaluation criteria. If this is not done, the tests will be confusing and not comparable. A large area fulfills the statistical requirements, but the trade off is increased process time and, consequently, increased cost for the test. In addition, large amounts of data are generated which require extra storage capacity. A too small area may cause the algorithm to not distinguish important features from noise, resulting in wrong interpretation. The size of the test area is determined by the magnification. Optical test methods are mostly specified for 30x to 100x magnification. The ASTM D2663-88 (ref. 31) Method B as one example, specifies a magnification between 75x and 100x.

* Definite instrument settings. If a test instrument is used only for experimental purposes, the instrument settings must be variable within the range of interest. This is especially important during evaluation and verification of a proposed test method. However, as soon as the test method has been approved, any instrument intended for tests according to that particular test method must, with no exception, follow the technical specifications. If a test is used for quality management, it should not be possible to change instrument settings (unless this is specified in the test method), alter automatic calculation procedures or tamper with calculated (processed) data. Most of the work in developing tests is to identify and avoid uncontrolled influences mainly due to human actions which, therefore, should be kept at a minimum. One parameter which clearly affects the dispersion rating is the degree of magnification (ref. 40).

Scope of work

The objective of this study was to test the new developments described elsewhere (ref. 39) in full scale trials by an independent rubber manufacturer. It would be of particular interest to find relationships between the measures possible to achieve with the automatic dispersion test system, the mixing quality and the actual results in the final manufacturing of rubber components.


The items listed in the previous section represent fundamental requirements when developing a test system for automatic classification of particle dispersion in rubber compounds. The instrument and corresponding dispersion standards used in this test are based on the International Standard ISO 11345. The new instrument series has been subjected to a thorough test program involving inter-laboratory tests and replicated multi-factorial performance tests of repeatability and reproducibility. All test methods have been approved by an independent, accredited research station, the Swedish Institute of Fibre and Polymer Research (IFP) in Gothenburg. The system comprises the instrument, including necessary software for data processing, data storage and communication, and five different dispersion standards for the polymer/ filler system to be evaluated.

Instrument for automatic classification of dispersion and large agglomerates

The tests were performed with a DisperGrader Model 1000NT with 100x magnification equipped with dispersion scales according to: The carbon black(x,y)-method; the reinforcing carbon black RCB(x,y)-method; the semi-reinforcing carbon black SRCB(x)-method; and the EPDM(x)-method. Before and after the test the instrument was calibrated according to the manufacturer's instructions using the 0.6 ISO certified standard grey photographic standard specimen. The x- and the y-values represent a dispersion number and a rating of the presence of large agglomerates, respectively.

The x-value is a dispersion number based on a scale graded from 1 (very poor) to 10 (excellent) dispersion. The most used test method is the carbon blacks CB (x)-scale for black rubber in general. The dispersion standards in reduced size can be seen in figure 3. If more accurate measures are needed, the CB(x)-scale is divided into two overlapping scales based on different carbon black types. The reinforcing carbon blacks RCB(x,y)-scale corresponds to the lower, coarser part of the CB(x)-scale and the semi-reinforcing carbon blacks scale which corresponds to the smoother (finer) part of the CB(x)-scale. The EPDM(x)-scale represents a further narrowed scale, based on the SRCB(x)-scale, particularly designed for EPDM-rubbers.


The y-value which rates the presence of large agglomerates is also based on a scale of 1 to 10. The y-value is, however, not based on visual comparison against photographic standards, but based on the actual size and number of large agglomerates. A high rating, 10, means that there are no agglomerates present in the tested area that are larger than 25 [micro]m in average diameter.

Test procedure

Specimens were prepared using the specimen sample cutter. An unused part of the cutter blade was used when cutting test pieces from the samples. Prior to tests with a different rubber compound, the instrument aperture was rinsed with cotton soaked in oil free acetone. Each reported value is the average of five replicated scans. The test procedure was as follows:

1) A test piece is cut from the sample, placed in front of the instrument aperture and firmly pressed against the same. 2) The appropriate scale is chosen. 3) Focusing. 4) The automatic dispersion classification function is activated. 5) The test is performed by starting the first scanning. 6) The scanning procedure is repeated by repeating item 3 to 6 to achieve five independent measurements. 7) Activate the automatic average calculation. 8) Record the process result. 9) Record the dispersion image.

Data acquisition was performed with an external PC and a special data communication program. Dispersion images were stored and transformed into tagged image file-format (TIF) with the same software. The TIF-format allows dispersion images to be inserted in test reports and spread sheets for documentation.

Materials tested

To analyze the efficiency of the dispersion test system, four different rubber materials were tested:

* A 65 Shore A peroxide cured EPDM compound for extrusion;

* a 62 Shore A sulfur cured NR/IR compound for extrusion;

* a 50 Shore A sulfur cured EPDM injection molding compound; and

* a second 65 Shore A peroxide cured EPDM compound for extrusion.

The compositions of the tested materials are summarized in tables 1-4. All compounds were mixed in a production mixer with a net volume of 72 liters and intermeshing rotor system.

Table 1-extrusion compound 65 Shore A
Ingredient Phr Note

EPDM 100
Carbon black 150
Plasticizer 60
Curing system Peroxide

Table 2-extrusion compound 62 Shore A
Ingredient Phr Note

NR/IR 100
Carbon black 60
Plasticizer 16
Curing system Sulfur

Table 3-injection compound 50 Shore A
Ingredient Phr Note

EPDM 100
Carbon black 140
Plasticizer 100
Curing system Sulfur

Table 4-injection molding compound 65 Shore A
Ingredient Phr Note

EPDM 100
Carbon black + clay 160
Plasticizer 60
Curing system Peroxide

Tests No. 1 to No. 6 were performed on unvulcanized stock, whereas tests No. 7 to No. 9 were made on material from cured test pieces (buttons) vulcanized for six minutes at 177 [degrees] C.

Test No. 1 was made on samples taken directly after the dump of the batch out of the internal mixer and test No. 2 after one pass through the mill gap of 2 mm. The 72" mill was run at 30 m per minute. Tests No. 3 to 6 were made on finely milled rubber stocks.

Fresh cuts were made with an unused part of a razor blade. All dispersion testing was performed with the light parallel with the direction of the cut. Care was taken in rinsing the specimen stage before a new compound was tested to avoid contamination of even thin layers of foreign substances.


The test results are summarized in tables 5-8 and figures 4-17. As can be seen in table 5, there is a significant difference between the dispersion values of the directly dropped batch compared to the dispersion level after one pass through the mill.


Table 5-extrusion compound EPDM 65 Shore A
Test no. CB(x)-value

 1 Directly dropped 0.1-3.7
 2 One pass through the mill 3.8-4.4

Table 6-extrusion compound NR/IR 62 Shore A
Test no. Speed Time Dump

 3 High Medium High
 4 Low Long Low
 5 Low Medium Low
 6 Medium Short Medium

Test no. Way of CB(x)-
 mixing value

 3 Convent. 7.5
 4 Convent. 7.2
 5 Convent. 7.4
 6 Upside down 7.4

Table 7-injection molding compound EPDM 50 Shore A
Test no. Speed Time CB(x)-value

 7 Low Long 5.2
 8 Medium Medium 5.1
 9 Fast Short 5.3

Table 8-extrusion compound EPDM 65 Shore A
Mixer Comment CB(x)

Old Conventional, 5.1 [+ or -] 0.2
 long mixing time
Old Conventional, 5.0 [+ or -] 0.2
 short mixing time
Old Upside-down, 5.0 [+ or -] 0.2
 short mixing time
Old Upside-down, 5.2 [+ or -] 0.1
 medium mixing time
New Conventional, 5.2 [+ or -] 0.1
 medium mixing time

Mixer EPDM(x) Maximum
 scale part size

Old 1.0 [+ or -] 0.5 46 [micro]m
Old 0.7 [+ or -] 0.5 52 [micro]m
Old 0.7 [+ or -] 0.1 52 [micro]m
Old 1.1 [+ or -] 0.1 40 [micro]m
New 1.1 [+ or -] 0.1 37 [micro]m

Mixer Surface

Old 80%
Old 65%
Old 65%
Old 90%
New 100%

In tests No. 3 to No. 6, no significant differences in dispersion numbers could be seen in measured dispersion values.

Regarding the presence of large agglomerates, significant differences can only be seen in analyzing the histograms. This is clearly shown in test No. 3, which showed the best dispersion rating, x-value. However, this batch was subsequently found not to be good enough for processing because some agglomerates caused defects during extrusion. Analyzing the figures 10-13 shows the presence of agglomerates including and larger than an average diameter of 57 microns in test No. 3 - 6. The best particle size distribution is found in test Nos. 6, figures 9 and 13. The latter was mixed in the shortest mixing time, i.e., medium rotor speed and was also rated the best among the trials in the extrusion test. Test Nos. 7-9 contained an injection molding compound (III) with a large sight area in single stage mixing. In this application, the maximum particle size is one of the most important parameters. Optimizing the mixing process is to produce good dispersion with short mixing times. The results of the test and the parameters varied in the test series are shown in table 7.

Table 8 shows results from a second extrusion compound, where the rubber mixture also was independently evaluated by an experienced rubber technician in extrusion and rated on a scale up to 100% surface quality (excellent) by visual inspection. The evaluation criteria in this case are based on experience and not linked to a specific standard.


Rubber manufacturing involves a large number of parameters that affect the end result. Most of these variables are interacting and impossible to separate in normal processing conditions. The only way to find correlations with the end properties is systematic testing in connection with long experience of rubber mixing.

One typical example of this is extrusion. In extrusion, the line speed may range from the order of mm' s per second (e.g. large rubber cross sections like tire: treads) compared with 50 m per minute for a window seal with an intricate cross section. Another related area is injection molding, which usually involves much higher shear rates. These differences in requirements call for different mixing procedures as well as different methods of measuring and controlling the same.

In the case of tire treads, the measure and surface appearance of the extrudate are less critical, since it will be further processed in subsequent operations, compared with the extrudate emerging when processing thin cross-sections. In the latter case, it is not possible to correct the surface finish in the subsequent continuous vulcanization in hot air, salt baths or by microwaves. Furthermore, the physical properties of interest are totally different: Sealing surfaces in static applications do not require the same level of, e.g., tensile strength and tear resistance usually required for good wear resistance which is the case for tire treads.

We decided to perform the investigation in a full scale experiment because the test, after all, is intended to be important for managing the mixing process. Of course there is always the problem of not being capable of controlling separate parameters like in laboratory experiments, but on the other hand, if these parameters can not be individually controlled in production, they are, from the mixing manager's point of view, only of academic interest. Most of the tests were performed on unvulcanized rubber. This is not always possible due to entrapped air which may affect the test result.

In this investigation, we found that when manufacturing rubber materials for extrusion of critical components, the conventional matrix methods do not possess the accuracy needed to distinguish between batches with good process capability and those with poor performance.

If, on the other hand, the simple rule to abandon all batches with agglomerates larger than 40 [micro]m was applied, the prediction of the quality of the final extrudate could be predicted with good accuracy. In figure 17, the maximum average agglomerate diameter is plotted against the surface quality, the latter an independent evaluation of the mixing quality in this particular case, made by an experienced manufacturer of extruded profiles. Although the test is subjective, not only the order in which the quality is rated is the same, there also seems to be an almost 100% correlation between the two test methods. This means that the image classification system makes the same judgements, i.e., uses the same evaluation criteria as the experienced rubber technician.

Dispersion testing has for a long time been one part of quality control in tire manufacturing. The dispersion number may be rated according to, e.g., the ISO 11 345 and ASTM D2663 test methods or compared to the tire manufacturer's own standards based on the matrix-method like the ASTM D2663 standard. By matrix-method is meant a method which rates the dispersion (particle distribution) as one dimension and the occurrence of large agglomerates as a second. The filler dispersion is evaluated and characterized in two numbers which also may be weighted together into one single rating. In this case, usually only the end physical properties of the materials are concerned. Examples besides tires are tire tubes, engine mounts and down-hole oil seals. It is a convenient way of testing, since single numbers are produced in a format that allows for simple comparisons with other test data, but also serves as a process parameter in closed-loop process management systems.

In case of, e.g., window seals, or similar products, the interest when judging the mixing quality is focused on the processing performance of the batch. This manufacturing is a highly competitive area involving continuous processes. The start up time until the production runs smoothly for such manufacturing may well be a matter of hours. Each new batch that is entered, if not carefully specified, means a risk in entering a compound with slightly different process properties. The outcome is usually variations in measure or surface appearance of the extrudate.

Doing the right thing from the beginning always pays off. However, what exactly the right thing is varies according to the end application. In this investigation, we have found that it is necessary to treat the evaluation of mixer performance in two categories: The physical properties and the processing properties of the rubber compound. The test instrument used in this investigation allows for this characterization.


By image analysis of a fresh cut rubber surface and a software for classifying agglomerates in number and sizes, it is possible to predict the extrusion performance of a rubber compound. In this investigation, rubber mixes that contained no agglomerates larger than 40 [micro]m in average diameter showed excellent process performance in continuous extrusion of thin cross sections. Mixes with agglomerates larger than 40 [micro]m showed various degrees of surface defects, increasing with agglomerate size and number. The result coincides well with the judgement made by personnel experienced in visual dispersion testing, which makes the automatic dispersion test system an efficient tool for mixing optimization.


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Author:Nilsson, L.
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Geographic Code:1USA
Date:Mar 1, 1999
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