State-of-the-art gel detection and quality reporting for EPDM products.
The integrity and appearance of finished articles depend on them being defect-free. For example, automotive manufacturers are setting and demanding ever stricter standards for the surface appearance of visible parts. Suppliers are finding that to meet these expectations they must incur a significant cost in scrap product and in quality testing. An effective strategy to minimize scrap includes employing the highest quality raw materials.
Polymer quality is largely determined by manufacturing process design and operational excellence. It is also critical to have a method to detect defects to best assure quality. Often, EPDM and other elastomer polymer suppliers are challenged to accurately measure gels and contaminants in their products. A way to improve the reliability and efficiency of defect testing is to automate the process, particularly by the use of an optical scanner (line camera) and analysis system.
Traditional methods of defect detection have used compounding and fabrication of articles followed by manual inspection. Such manual methods are time-consuming and require significant amounts of personnel time, but more importantly can be variable due to operator and test biases. Another complication is that there is no standardized test methodology broadly accepted across the industry.
To meet the ever increasing demands for quality by customers, this article discusses state-of-the-art gel test methodologies used by Dow Chemical for Nordel IP hydrocarbon rubber (EPDM polymer) products. Additionally, a scientifically based approach to reporting absolute defect levels is discussed and is related to other industry standard tests.
This article discusses gel testing, as well as the methodology and the capability in measuring gels in EPDM polymers. A new machine vision gel/contaminent detection and reporting system was recently developed by Dow for EPDM polymers to the latest state-of-the-art standards. As a first for the EPDM industry, gel quality is now being reported on the certificate of analysis for all Nordel IP branded products. This methodology is also intended to increase the transparency of this critical analysis for the industry to enable the end-user to achieve measurable higher quality and associated lower manufacturing costs. A previous work discussed methods used for the gas phase process granular MG EPDM products (ref. 1).
The distinct metallocene catalyst and process technologies pioneered by Dow for EPDM polymer production are ultra low gel process (ref. 2). Consequently, gels are rare events which require a reliable and sensitive detection method including frequent testing and statistically large enough samples to best assure product quality and consistency in processing and end-use performance.
Machine vision technology has been demonstrated to be a proven way to characterize gel (and contaminant) quality and is also well proven in transparent polyethylene (PE) products such as films. Dow Chemical produces Nordel IP in Plaquemine, LA, to the highest quality standards. There has been a continual and dedicated focus on gel and quality testing of production since the plant start-up in 1997. This represents 13 years of experience in effective gel testing, including more than 10 continuous years of automated optical testing.
A gel detection method adapted from Dow polyethylene (PE) film technology was developed and first introduced in 1999 to qualify EPDM production. An upgrade to the latest Dow global most effective technology (MET) for PE was completed in 2008 using the latest state-of-the-art optical detection system.
Optical testing is superior to the industry standard tests ("IST") which are based on visual observations and assessments of a test compound extrusion method. The optical method was found to be more objective and consistent, minimizing operator bias and variations.
The optical scanning technology is used on clear polymer tapes. Neat polymer is sampled directly from the production process. Thin, clear tapes are formed by extrusion from the melt and used for analyses. Extrusion conditions were developed to match the shear range of internal mixers typically used in the rubber industry. Defects are accentuated by drawing the tape down to a thin thickness.
Analyses are conducted continually (24/7) during production and intended to be completed before product is packaged. This allows for the exclusion of any sub-standard batches before packaging and the opportunity to more rapidly respond to possible production events.
The present gel limits have been re-specified to a more rigorous specification and methodology. Results are analyzed and reported on a more sensitive part per million volume (ppmv) basis that emphasizes large particles which are more likely to cause defects. Sampling from the process is intended to minimize material handling and possible spurious contamination.
The optical test method has been proven to be highly reliable, consistent and correlatable. Full time on-site support is available along with the other associated PE film test systems on site. Test methodology follows the rigors of the Dow analytical methods (DOWM) and is capable of becoming a new industry standard test.
In fact, the optical gel test method has demonstrated excellent reliability. Over 500,000 MT (> 1 billion lbs.) of EPDM products have been qualified to date. Significantly, no gel issues or complaints have been reported by customers using the highest quality materials specifically specified for Class A automotive weatherstripping applications.
Now, all Nordel IP rubber grades are uniformly qualified at the highest quality specifications. Since early 2009, and as a first for the industry, gel quality of the product is reported on the certificates of analyses (CoA) sent with each batch.
This article focuses on the optical detection and reporting methodology used, as well as the instruments and the capability in measuring gels in EPDM polymers.
Excellent surface quality or Class A surface for automotive use includes parameters such as gloss, surface smoothness, color uniformity and the absence of surface defects. Additionally, the level of expectation for surface quality has increased over the past decade and undoubtedly will continue to increase into the foreseeable future. While there is general agreement that surface imperfections, including gels, are unacceptable, there is not full agreement across the industry of the exact performance boundaries for the various surface parameters for rubber parts.
Not all consumers cite the visual quality of the various rubber profiles in an automobile as a selection criteria for purchase; however, their appearance must not detract from the general quality of the vehicle. These defects include color, inconsistent gloss or matteness, and uneven surfaces within a part. Defect-free aesthetic and structural considerations are becoming more important.
A fishbone analysis of some of the root cause factors that affect surface quality is shown in figure 1. While there are many potential root causes, it is obvious that if the incoming raw materials are flawed or contaminated, then the challenge can be significant to produce an article with high surface quality.
To provide the greatest level of quality to the compounder with EPDM polymer, the supplier must rigorously inspect and drive their process to minimize defects of any kind. As an example, a series of voice of the customer interviews was held to quantify the relative rates of the various causes and is summarized in figure 2. The presence of gels in incoming EPDM is a significant concern in defects in surface quality. The rejection rate was also found to vary considerably between compounders and geographies. In any case, there is considerable cost in the lost raw material of unusable parts, lost productivity, disposal and the lost worker time trying to monitor and improve users' processes.
[FIGURE 1 OMITTED]
In the manufacturing of EPDM polymer, some processes and technologies are more favorable for the production of ultra-low gel EPDM. As a general guideline, the lower the energy, heat input and fewer steps in the process, the lower the chance of gel formation. Metallocene catalysis, a sub-set of which includes constrained geometry catalysts (CGC), is a key technology advance because the very high catalyst efficiency does not require a de-ashing step and it is relatively simple to de-activate the catalyst. In addition, a state-of-the-art solution process plant operates without steam injection, and therefore without the localized heating of the product that often causes gel formation.
Polymer quality is instituted through the design and operational excellence of the manufacturing process. The operations and processes for the plant need to be continuously and extensively reviewed and revisions made in plant production as needed to improve and optimize quality to drive to ultra-low gels. This includes operating discipline around raw material streams, including catalyst, monomer, materials handling and logistics.
All manufacturers still have in common a need for a meaningful gel quality method to ensure that their customers receive only top-quality elastomers, as well as the ability to demonstrate and document this on a per lot analysis. Gels, contaminants, product uniformity and packaging are key areas of focus in quality. This article focuses on the detection and reporting of gel quality in the final polymer product.
Results and discussion
Typical measurement of gels
Gels in elastomers typically are measured using visual methods which are most often manual, cumbersome and subjective. In many compounding plants and extrusion factories, a length of extruded profile is inspected by eye and judged to be good or bad. The inspector may know what is usually tolerated by their individual customers and they will pass/fail the profile or compound accordingly. Some automotive profile producers have developed tests based on visually inspecting an extruded tape and assigning points or limits to the size and hardness of the defects in a "gel number" or "gel rating."
[FIGURE 2 OMITTED]
These traditional defect detection methods require compounding and fabrication of articles, followed by manual inspection. Such methods are time-consuming and require significant amounts of personnel time, but more importantly, can be variable due to operator bias and are prone to contamination. Such tests involve mixing a formulation typically containing carbon black and plasticizer oil, then extruding the compound into a tape, and visually inspecting any surface defects by eye or under a microscope.
There are other factors that can contribute to variability of such testing. Sampling and specimen sizes are limited to the mixer batch size and the amount of tape that can be conveniently inspected. Operator bias can occur due to vision and lighting differences and interpretation of the character and size of the defects. The gel defects are not directly visible, but depend on their visibility as surface disruptions in an opaque tape. Detection limits depend on the thickness and surface quality of the tape and the viewing angle. Classification depends on skilled practitioners, including cutting into and removal of the defect.
Inadvertent contamination with these compound methods is a risk due to the numerous compounding ingredients, and handling and process steps. This requires the lab, mixing and processing equipment (mill and extruder) to be exceptionally clean. Meticulous skill and care are also required by the operators.
In addition to the complications and sources of variances in traditional gel testing with a compound, there does not appear to be an agreement on uniform standards in the industry for gel or defect rating or count or even defect size, tape thickness and exact formulation. The industry may be better served if there were such a standard. The use of an automated optical method potentially can provide such an improved standard method.
Defect analysis using an optical scanner in transmission mode
In contrast to the rubber industry, there are several commercially available instruments and methods in the plastics industry designed for monitoring the quality of polyethylene (PE) polymers by detecting gels and/or defects for the film packaging market. Dow and other major PE producers have adopted machine vision technology to measure the defect quality in their polymers. The adaptation of this technology to meet the demanding requirements of measuring gel for commercial EPDM polymer production is discussed in the following sections. This technology has proven to be essential to ensure the highest quality ultra-low gel polymer for about a decade.
[FIGURE 3 OMITTED]
The operating principles of an optical method are based on a system that measures defects in a transparent polymer film or tape that requires a light source; a line camera; a meter to measure linear displacement; and a software package that can translate and capture the data to a usable form. Such components are illustrated in figure 3. A simple way to look at this is that the linear displacement meter, which measures the x direction, and the camera, which measures the y direction and the z direction, can generate a three-dimensional image of the defect. The current equipment in use is illustrated in figures 4 and 5 and shows the key components of the gel quality test system and shows a running thin tape sample.
[FIGURE 4 OMITTED]
[FIGURE 5 OMITTED]
The process for obtaining a usable structure from which to measure for gels involves adding the polymer to an extruder which melts and extrudes a uniform structure. The film passes from a light source, through the sample and into a camera assembly where an image is captured and digitally processed. EPDM polymers have relatively low or no crystallinity, making them transparent to the light source, and the defects are measured in the transmission mode.
The light source is a light emitting diode (LED) which has a long lifetime and is stable in its light intensity output. The light is in the visible range. The intensity needs to be sufficient to allow the camera to differentiate changes in transmittance if the film is somewhat translucent.
The line camera scans a finite width. This can be viewed as the y direction. The camera is high resolution. The camera also detects transmittance differences in the light as it passes through the base or background material and the defect. This can be viewed as being the z direction.
The software package can take the x, y and z data, as described above, and analyze the results. In order to illustrate the power of machine vision, information can be measured to recreate a three-dimensional image of a defect which can be viewed from various perspectives.
An optical system can detect any particle or defect that falls within its detection range. This range can be beyond that of the unaided eye. In addition, calibration and standardization can be easily conducted.
To illustrate the capability of an optical detection system, various items were examined as they passed under the camera. One example is a laser-printed letter in a small font. Figure 6 on the fight shows the transmission micrograph of the printed letter "A." The left photo in figure 6 is the 3-D representation of the letter as detected by the camera. As can be seen, there is excellent agreement between what the eye sees under a microscope and what the camera can see, including the printing defects in this letter.
Importantly, the camera can detect transparent as well as opaque defects. Since these optical systems can detect a defect by the difference in light transmitted to the camera from the background film versus a defect area, then the difference may be useful in determining if a defect is either opaque or transparent. The focus of this paper is on typical clear polymer gel defects.
[FIGURE 6 OMITTED]
The more challenging case is that of a transparent particle such as a gel particle, glass bead or grain of sand, that are generally not easily seen by the eye in a transparent matrix. If the index of refraction for the defect is the same as that of the polymer, such as in the case of a transparent gel, the defect most likely will not be seen well by the eye in a transparent tape.
If the tape or film is elongated in the melt, the polymer around the defect flows differently or elongates differently than the bulk polymer. This amplifies the appearance of the defect and makes visual and camera detection easier. If the defect is a clear particle, it is generally seen visually as a dark circle with a clear center in the film or tape. This process is depicted in figure 7.
Thus, a clear transparent gel in a tape can be detected by an optical device. A change in transmittance is detected and can be represented. As a reference, a transmission micrograph of a clear gel particle is shown in figure 8. The gel appears as a dark circle with a clear transparent center.
The same gel defect is shown in figure 9 as measured using an optical camera. The data and 3-D graphics for the image are also given in figure 9. The graphics size and shape presented by the optical acquisition system are almost identical to those of the gel seen under a microscope.
[FIGURE 7 OMITTED]
[FIGURE 8 OMITTED]
Correlation of the optical method to industry standard test
To determine a correlation between gel counts on clear tapes obtained from the optical scanner system and the industry standard test ("IST") that uses a traditional formulated compound "gel number" rating, several calibration samples having various gels ratings were run using both methods. A standard formulation for gel testing was used and scaled to a 00C size Banbury tangential-type internal mixer, as well as a 9.4 liter Werner & Pfleiderer intermeshing mixer. Following a standard method, the materials were mixed, roll milled, stripped extruded into
a tape, and all defects observed in 30 meters of extruded tape are marked. Defects such as undispersed carbon black, grit, fibers and other identifiable non-polymer contamination were not included in the rating.
By the prescribed method, if the number of defects is less than 30, all defects are examined under a microscope. If the defects are more than 30, only 30 are examined and the total gel rating is scaled upwards based on the 30 investigated. These defects were classified into "hard gel," "soft gel" and other categories, each with a relative weighted number multiplier. The character of the gel particles in this study was most typically soft gel.
From considerable prior customer experience, a calculated "gel number" of 30 or less is considered "best in class" and a rating less than 100 is required before the material can typically be used in automotive weatherstripping applications. Thus, this limit can at most be a few "soft gel" defects and no "hard gel" defect. Of course, no gel defects at all are preferred.
[FIGURE 9 OMITTED]
A good correlation of these methods was obtained, as shown by a correlation plot of the data in figure 10 for a series of calibration polymer samples run using both IST gel and optical analysis methods. The correlation is very good and was best modeled using the greater than 400 micron ([micro]m) data from the clear tape gel data to that of the compound gel rating. The limit of unaided vision is about 400 microns. Thus, the greater than 400 microns particles can be used in the clear gel tape test. By this method and using this scale for the optical test, a material must have seven or fewer polymer particles greater than 400 microns via the clear tape gel test to be rated acceptable for weatherstripping (WS). Also significant, there were no false negatives or false positives for the best WS quality materials in this study using this scheme.
In conjunction with recent test developments and the upgrade of the optical equipment, a new mathematical formalism was introduced to better understand and improve, as well as simplify and speed the detection and reporting of the level of gels in a system, and it is discussed. When developing the best formalism for reporting a composite gel or defect level, some kind of boundaries and computation must be established to account for the various potential sizes of defects that are measured.
In the production of an extruded profile part, a gel or defect will manifest itself as a surface blotch. For most applications, the presence or absence of a moderate surface imperfection does not typically alter the part's actual physical performance, thus the lower boundary for the analysis need only extend to the range where the unaided eye could detect a surface imperfection. The upper limit of detection is essentially unbounded. The larger and visible gel defects are, in practice, of most concern.
Some possible strategies for reporting product quality include:
* Qualitatively comparing a test structure to an array of standards and assigning a quality rating;
* listing every defect in a test sample by size and number;
* counting all the defects, irrespective of size, and reporting the sum; and
* applying a scaling factor to each defect and reporting a composite value.
[FIGURE 10 OMITTED]
In fact, the approach taken was a hybrid of all four of these approaches to upgrade the sensitivity and capability of the optical test.
The image software can perform Nob analysis on the binary image in which adjacent black pixels are associated with an individual "blob" or defect. The area of each defect is simply a function of the number of pixels in each blob. Many metrics can be used to describe the size of the defect, e.g., longest dimension, perimeter length or defect area. A common metric employed is the Equivalent Circular Diameter (ECD), in which the diameter assigned to the defect is calculated by determining the diameter of a circle with the equivalent area. Using simple geometry, the diameter can be projected to a volume of a sphere. This transformation is shown in an example in figure 11.
The image is digitized and, in this example, there are 28 pixels in the object (blob). Given a resolution of 50 microns ([micro]m), each pixel has an area of 2,500 [micro][m.sup.2]. The object thus has a diameter (ECD) of 299 [micro]m and a silhouetted volume of about 13,900,000 [micro][m.sup.3]. As calculations are applied consistently, this tends to cancel out any inconsistencies in the analysis.
By measuring the length, width and thickness of the test sample and combining this with the composite volume of measured defects, a straightforward volume of defects may be calculated by the following equation,
[ppm.sub.V,j] = [k.summation over (l)] [V.sub.j,k]/[L.sub.j][W.sub.j][T.sub.j] x [10.sup.6]
where the composite parts per million volume, ppm(v) of defects may be expressed for the analysis cycle j. This accentuates the larger defect particles that are most likely to cause visual or structural defects in the final fabricated parts. Since defects are typically rare or none, the error (noise) is reduced by either averaging multiple analyses or by simply increasing the sample size used for each analysis cycle.
[FIGURE 11 OMITTED]
To further illustrate this approach, consider a sample with the four gels listed in table l, in the size range of micro, small, medium and large. As there are only four gels in total, each contributes 25% to the total count, as shown in figure 12. However, the increasing influence of the larger gels is revealed when comparing the relative contribution of each gel to the area and volume totals. Thus, the new methodology provides a more discriminating determination than the same previous gel count method.
In addition, the use of this formalism is demonstrated in figure 13 where a series of polymer test samples was evaluated and repeated using a conventional compound IST methodology and the currently described machine vision computer controlled ppm(v) analysis. As is apparent, the standard deviation for the ppm(v) analysis is significantly lower than the conventional method, in this test case, 0.67 vs. 1.43, respectively. A low level of background noise remains. As can be expected, the use of machine vision can provide consistency within a single data set and can provide superior consistency from year to year, ensuring long term quality detection reliability.
There has been a continual and dedicated focus on gel and quality testing of EPDM production at the Dow Plaquemine, LA, plant since start-up in 1997. New optical testing equipment was implemented in late 2008 using the latest state-of-the-art Dow global polyethylene (PE) technology using a new optical detection system. The components, methodology, elements and capability have been improved and replace the previous optical system that was used for the last ten years. A more sensitive lower size limit (>200 [micro]) and the new part per million volume, ppm(v), reporting scheme is now used in the analyses.
[FIGURE 12 OMITTED]
[FIGURE 13 OMITTED]
Analyses are conducted continually (24/7) during production. This allows for the exclusion of sub-standard batches and the opportunity to more rapidly respond to possible production events. Twenty-four (24) hour on-site support is available along with the other associated PE film test systems on site.
The new optical method correlates very well with the previous optical system. A new uniform specification limit has been established at <12 ppm(v) units for best EPDM product quality. This specification value has proven to be acceptable in demanding applications. The analysis is conducted in near real time with the capability to analyze and qualify product before packaging. Significantly, the result for each branded Nordel IP production batch is now shown on the certificate of analysis (CoA), a first for EPDM products.
The optical gel test methods continue to demonstrate excellent reliability. Over 500,000 MT (>1 billion lbs.) of EPDM polymer products have been qualified to date. Significantly, gel issues or complaints have not been reported by customers with the "best" quality grades directed to automotive weatherstripping applications, previously designated internally as weatherstrip (WS) or "extra-clean" (EC) quality. Now, all branded material is the best quality.
Current product quality remains excellent. Figure 14 shows the gel quality trend for best quality EPDM grades for the last few years to the present (2006-2009), and shows a process well in control and one that can meet the highest quality requirements in the industry. As shown, the use of machine vision in the Dow gel test provides consistency of quality detection and rating from year to year, ensuring long-term customer quality and satisfaction with ultra-low gel EPDM products against some of the most demanding requirements in the industry.
Comparison with other industry tests
Comparisons can be made between the present Dow optical method gel test and other tests used in the industry. The German rubber industry association, Wirtschaftsverband der Deutschen Kautschukindustrie (WDK), and the vehicle manufacturer BMW have standard gel/defect tests that are performed on finished automotive weatherstrip profiles, designating the best Class A quality, as well as lesser Class B quality. Parameters and requirements for the WDK and BMW tests are summarized in tables 2 and 3, respectively.
[FIGURE 14 OMITTED]
The WDK test 2101-1 involves the visual observation of a 400 [cm.sup.2] area of weatherstrip from 50-70 cm distance. The person testing the weatherstrip has five seconds to make the observation. There may be no more than one large defect, two medium and four small defects in a Class A surface, and two large and four medium on a Class B surface. The WDK test parameters and requirements are summarized in table 2.
A comparison between the WDK 2101-1 test and the present Dow gel test can be made. As an example and for comparison, three assumptions can be drawn:
* The tester sees all the defects in the part (this may not be likely in five seconds);
* all the defects in the elastomer compound are present at the observed surface (this assumption may in fact be wrong by a factor of two or more, depending on the thickness of the part); and
* the compound comprises 33% volume elastomers, the rest being other compounding ingredients. In fact, typical compounds can comprise only 15-25 volume % elastomers.
Therefore, a Class A visible surface can be passable if the profile contains under about 50 ppm(v) of defects. It is expected that, even under other assumptions and circumstances, EPDM polymer that passes the Dow test is extremely unlikely to cause sufficient defects to cause the compound to fail the WDK test.
A comparison with the BMW test shows that this test is more demanding. The BMW test parameters and requirements are summarized in table 3. Again, some assumptions are required:
* In the worst case, the observer may spot all the defects (again, may not be likely in five seconds);
* thin profiles or veneers may allow most defects to come to the top of the surface, but a factor of two is a reasonable assumption; and
* the compounds contain 33 volume % elastomers (again, this assumes a polymer rich formula).
Thus, a polymer is estimated to have under about 15 ppm(v) of defects to pass the Class A requirements at BMW. If we examine the assumptions made, the 12 ppm(v) of the Dow test is a reasonable level set capable for a pass/fail criterion for one of the most demanding industry requirements.
We can therefore translate the <12 ppm(v) limit of the Dow test to a contribution from the elastomers component of the compound part under the requirement for both the WDK and the more demanding BMW test requirements. Thus, the compounder has a safety factor for the other causes of defects such as from the carbon black, from dust, etc. This margin for error translates directly into quality assurance for the compounder, extruder and vehicle manufacturer. The derived Class A requirement levels from the WDK and BMW tests are shown in the trend plot in figure 14 as a reference.
EPDM product applications are setting ever stricter standards for defect reduction and elimination, including the surface appearance of visible parts. Customers and compounders are finding that to meet these expectations, they must incur a significant cost in scrap product and in quality testing. An effective strategy to minimize scrap includes employing and relying on the highest quality raw materials. To meet the increasingly demanding quality needs of customers, a state-of-the-art gel test methodology based on an automated optical detection system was developed and is used by Dow Chemical for EPDM polymer production.
The distinct metallocene catalyst and process technology pioneered by Dow for EPDM polymer production is an ultra low gel process. Consequently, gels are rare events which require a reliable and sensitive detection method including frequent testing and statistically large enough samples to best assure product quality and consistency in processing and end-use performance.
Machine vision technology has been demonstrated to be a proven way to characterize gel and contaminant quality, based on ten continual years of EPDM production and testing experience. Over 500,000 MT (> 1 billion lbs.) of EPDM polymer products have been reliably and consistently qualified to date. The optical test method has been proven to be highly reliable, consistent and superior to traditional laborious and variable methods using visual inspection of opaque compounded pro files. The optical scanning technology uses clear polymer sampled directly from the polymer production process to minimize any possible contamination.
Improved optical equipment and methodology for detecting and reporting gel quality have been recently developed and installed. The scheme allows for continual (24/7) analyses during production and allows for the rapid exclusion of any sub standard batches.
A scientifically-based approach to measure absolute defect levels was developed and is provided. The present gel limits have been re-specified to a more rigorous specification and methodology. Results are now reported on certificates of analyses on each batch of branded Nordel IP. The EPDM industry can be well-served by a transparent, objective machine vision methodology for such a critical-to-quality analysis. Comparisons with other industry tests can also be better developed.
The optical gel testing enables a consistent determination of product quality to best enable users and compounders to achieve improved efficiencies and reduced costs by minimizing scrap with incoming consistent and high quality EPDM polymer. The objective is to provide measurably high quality EPDM polymer in final products to achieve value.
(1.) T. Clayfield, J. Barclay, P. Kenny, R. Mangold and B. Walther, paper no. 10, "New methodology for high surface quality characterization in EPDM extruded compounds," presented at the Fall 174th Technical Meeting of the Rubber Division of the American Chemical Society, Louisville, KY, October 14-16, 2008.
(2.) S. Chum and K. Swogger, "Olefin polymer technologies-history and recent progress at The Dow Chemical Company," Progress in Polymer Science (2008), 33(8), 797-819.
by Arnis U. Paeglis, Larry A. Meiske, Ray A. Mangold, Pam J. Kenny, Brian W. Walther and Tim E. Clayfield, Dow Chemical
Table 1--an example of the influence of size on various gel metricsGel Pixels ECD, Area, Area, Volume, Volume, mm [mm.sup.2] % [mm.sup.3] % Micro 20 0.252 0.05 1.6% 0.008 0.3% Small 60 0.437 0.15 4.7% 0.044 1.4% Medium 300 0.977 0.75 23.4% 0.489 15.9% Large 900 1.693 2.25 70.3% 2.539 82.4% Total 3.20 100% 3.080 100% None 0 0.00 0.00 0.0% 0.000 0.0% Table 2--comparison of WDK 2101-1 gel test and the Dow gel test limits WDK 2101-1 gel test limits Translation to ppm(v) with Dow gel test Size Large gels Medium gels * Small gels Category 700 <[empty set] 400 <[empty set] 200 <[empty set] <1,000 <700 <400 [micro]m [micro]m [micro]m Class-A 1 2 4 Class-B 2 4 -- Dow Test Equivalent volume of gel in [m.sup.3] Category Large Medium Small [empty set] = 800 [empty set] = 400 [empty set] = 300 [micro]m [micro]m [micro]m Class-A 2.68E-10 1.31E-10 5.65E-11 Class-B 5.36E-10 2.62E-10 Category Vol. sum Total volume Est. limit, inspected ** p[micro]m(v) Class-A 4.56E-10 2.68E-05 ~57 Class-B 7.98E-10 2.68E-05 ~99 Notes: Profile of 400 [cm.sup.2], 5s visual inspection at 50-70 cm distance; S = 0.04 [m.sup.2] * should be 20 cm away from one another; * 0.67 mm based on the thickness of the Dow extruded tape ** based on a total volume inspected of 400 [cm.sup.2] Table 3--comparison of BMW gel test and the Dow gel test limits BMW gel test limits Translation to ppm(v) with Dow gel test Size Large gels Medium gels * Small gels Category 500 <[empty set] 300 <[empty set] [empty set] <1,000 <500 <400 [micro]m [micro]m [micro]m Class-A 0 1 2 Class-B 1 1 2 Dow Test Equivalent volume of gel in [m.sup.3] Category Large Medium Small [empty set] = 700 [empty set] = 400 [empty set] = 300 [micro]m [micro]m [micro]m Class-A 0 3.35E-11 2.83E-11 Class-B 1.80E-10 3.35E-11 2.83E-11 Category Vol. sum Total volume Est. limit, inspected ** p[micro]m(v) Class-A 6.18E-11 1.41E-05 ~15 Class-B 2.41E-10 1.41E-05 ~57 Notes: Profile of 3 cm by 70 cm, 5s visual inspection at 50-70 cm distance; S = 0.21 [m.sup.2] ** based on a total volume inspected of 400 [cm.sup.2] * 0.67 mm based on the thickness of the Dow extruded tape
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|Author:||Paeglis, Arnis U.; Meiske, Larry A.; Mangold, Ray A.; Kenny, Pam J.; Walther, Brian W.; Clayfield, T|
|Date:||Jan 1, 2011|
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