Service Life Prediction of Organic Coatings - American Chemical Society

Chapter 14

Analysis of Coatings Appearance and Surface Defects Using Digital Image CaptureProcessing-Analysis System 1

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Fred Lee , Behnam Pourdeyhimi , and Karlis Adamsons 1

Materials Engineer, Atlas Electric Devices, 4114 North Ravenswood Road, Chicago, IL 60613 Professor, Polymer Education and Research Center, School of Textile and Fiber Engineering, Georgia Tech, Atlanta, GA 30332-0295 Staff Chemist, Automotive Products, Marshall R & D Lab, DuPont Company, Philadelphia, PA 19146

Downloaded by CORNELL UNIV on October 8, 2016 | http://pubs.acs.org Publication Date: April 15, 1999 | doi: 10.1021/bk-1999-0722.ch014

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Durability and weathering studies of coatings involve accurate monitoring and meaningful analysis of the coating's appearance. The currently available techniques that monitor and analyze coatings are oftentimes deficient in accurate characterization of coating appearance. Furthermore, visual attributes that comprise the surface of interest are typically assessed by humans, making objective assessments laborious and difficult. Implementation of digital imaging in various scientific applications has been proven accurate and productive. The Video Image Enhanced Evaluation of Weathering(VIEEW) system has been developed at Atlas Weathering Services Group, Miami, in collaboration with Georgia Tech. In this report, applications concerning automotive top coat defects are presented using the digital imaging/image processing/image analysis instrument. The VIEEW data was also compared with conventional evaluation results. The VIEEW system demonstrates that the appearances changes and surface defects created by durability/weathering tests on automotive coatings can be visualized and quantified accurately. As regards to service life prediction(SLP) of organic coatings, meaningful visualization and precise quantitative surface measurement would undoubtedly further the effort to understand the complex kinetics of a material's chemical and physical property degradation, as well as mechanical performance changes.

Appearance property measurement is an important coatings evaluation (1,2,3,5,6,7). The word "appearance" refers to the measurement of the visual attributes of an object.

© 1999 American Chemical Society Bauer and Martin; Service Life Prediction of Organic Coatings ACS Symposium Series; American Chemical Society: Washington, DC, 1999.

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Unlike other material properties, the appearance properties are tied to human psychology. As with other subjective visual assessments, the results are often sensitive to biases in individual's perception. Recommended protocol often requires the estimation of size, shape and distribution characteristics by eye ~ perceptual judgments that are often tedious and time-consuming. The complex response of human perception can be, however, partially measured using photometric devices. While photometric devices can measure the amount of light reflected from the target area of an object, the spatial composition of the target area is still at a loss. Hence it would be desirable to develop automated instrumental methods incorporating two-dimensional imagery for evaluating coating integrity and measuring degradation. Digital imaging and image process/analysis techniques have been available for many years in the scientific community. From biology to metallurgy, imaging has routinely been applied in surface characterization and for monitoring the kinetics of changes in surface/component morphology. Its ability to gather visual information in two (and pseudo-three) dimensional format in a transferable digital file has been fully accepted. Also, its ability to "analyze" and "archive" the imagery only furthers the applicability. In weathering and durability studies of coatings, understanding surface deterioration and surface visualization is important. (9-20). While qualitative microscopic visualization techniques have benefited studies, quantitative macroscopic visualization techniques have not been readily available. The macro scale surface evaluation of coatings has been carried out by mostly human visual comparison techniques. Standard human visual comparison techniques used in the coatings industry include, but not limited to, visual color change, gloss change, general appearance, chalking, dirt retention, mildew growth, crazing, checking, rust, erosion, flaking, blistering, water spotting, discoloration and visual haze. Monitoring the onset of change in a coating's appearance, and subsequent kinetics of these changes, can often provide insight into the underlying factors such as chemical or mechanical performance degradation. This information may lead to a better understanding of the adverse impact of environmental factors, material properties, material processing, and application consideration^). Ultimately, a detailed understanding of the factors, and their respective impact, will help make meaningful service lifetime prediction a reality, as well as product design/modification more efficient. Quantitative macroscopic visualization using digital imaging and special illumination design (Video Image Enhanced Evaluation of Weathering, VIEEW) has been studied at Atlas Weathering Services Group in collaboration with BARN Engineering in 1993 and later with the Georgia Institute of Technology. Introduced by NIST to the organic coatings industry in the early 90's, this digital imaging technology has gained interest from various materials related and, especially, the weathering and durability related field for its robust and quantitative analysis capability.

Bauer and Martin; Service Life Prediction of Organic Coatings ACS Symposium Series; American Chemical Society: Washington, DC, 1999.

209 This paper describes 1) shortfalls of the conventional photometric appearance measurement techniques in weathering and durability applications, 2) the VIEEW system, and 3) the applicability of the VIEEW technology for automotive coatings durability studies, specifically in the visualization and the quantitative analysis of automotive topcoat defects such as scratch and mar defects, acid etch defects, weather induced cracking defects, and gravelometer chip defects.


Conventional Appearance Measurement Methodology I - Reflectance Based Photometric Measurements Specular gloss is probably the most important and recognized reflectance based photometric measurement technique used in weathering studies for the analysis of the top coat of automotive coating systems. While specular gloss can quantify the reflectance characteristics of an object, it is noteworthy that gloss values do not precisely describe surface conditions of interest, in the case of automotive coatings, the surface of the topcoat. A common problem in reflectance based photometry lies in the influence of chromatic attributes (color) in the measurement value. This problem can be easily illustrated by referring to Figure 1 where idealized goniophotometric curves of the photo current as a function of viewing angle are given. The curves S and u are goniophotometric responses of a perfect diffuse reflector and a semi gloss white coating, respectfully. From the schematics, a height of gloss, h is defined as h- P~

M45

_ P ~ S45

A 100

o o Ou

0°

30°

60°

90°

Angle of Viewing

Figure 1. Schematic representation of photocurrent as a function of viewing angle. (Reproduced with permission from reference 21, Copyright 1972 Elsevier.) Where, A is the relative brightness of the sample compared to a perfect diffuse reflector. By this definition, high gloss coatings have higher h values. From the


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schematics, however, one can see that the absolute value of p, the actual intensity of specular gloss, would not be the only determining factor in evaluating gloss. Here the numerator in the formula is computed by the differences between specular reflection and diffuse reflection of the sample. For example, two coatings exhibiting the same quantities of specular reflection would not necessarily have the same gloss value. A coating with a lower A value would have higher gloss value due to the diffuse dependency at the specular angle. Inspecting a black specimen and a white specimen of identical surface finish condition can easily demonstrate this phenomenon. Using a gloss meter, the black specimen would be rated at a higher gloss level than the white coating. While this result may agree with human visual perception, the results do not describe directly the materials' surface condition and may lead to inappropriate interpretation.

VIEEW Image Capture/Image Processing/Analysis System - Hardware An imaging system is comprised of largely two separate functional components. These are 1) The optical component (Image acquisition) and 2) The computing component (Image processing/analysis). The VIEEW system includes an image acquisition software unit and separate image processing/analysis software. It has been found efficient to install the acquisition and the processing unit independently for optimum operation. The optical component is comprised of illumination sources and focusing optics. The importance of light geometry cannot be overstated in photometric devices. For the VIEEW system, it is impossible to use conventional lighting schemes commonly used with commercial image capture and other photometric systems. Unlike the conventional photometric devices where a two dimensional optical arrangement is usually adequate, for coatings and other similar surfaces, we use a three dimensional optical arrangement where the focal plane is perpendicular to the optical axis in order to provide spatially even focusing. The main system characteristic of VIEEW is the availability of two distinct illumination schemes enabling geometric and chromatic viewing. It is well known that it is most discriminating (as far as reflectance or gloss is concerned) when light is directed to a surface at a low incident angle. The most ideal incident angle is 0°. This angle is particularly useful for capturing surface texture and roughness. When the light is directed to surface at 0° angle, it will be reflected from the surface at 0°. When a stream of light is reflected perpendicularly (0°)fromthe surface, the direction of reflection is confined to 0° if the surface is optically smooth. However, when the surface is not optically smooth, the light will be reflected from the surface at angles greater than 0°. See Figure 2.


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Optically Smooth Surface Optically Rough Surface Figure 2. The 0° incident light interaction. This scattering effect of reflected light is most beneficial in examining surfaces in the presence of dirt, scratches, and streaks (common in weathered surfaces). These characteristics render conventional gloss measurements unreliable. When the light is reflected at large angles caused by the irregularity of the surface the scattering would not affect image formation since it is not detected by the target receptor. Figure 3 is a composite of four automotive top coat images captured using the VIEEW system showing the off-axis scattering of scratch marks appearing as dark lines.

Figure 3. The scattering effect of 0° incident reflected light. The VIEEW system uses another illumination scheme that induces chromatic reflection (diffuse reflection). When a uniform, spatially integrated radiation distribution is required, an integrating sphere technology is commonly used. An integrating sphere is composed of two perfect hemispheres that are coupled together to form a spherical cavity. Also, the inner surface of the sphere is coated with a high reflectance substance to achieve a high degree of diffuse illumination. The VIEEW system accommodates a direct viewing path through co-axially-situated entry and exit ports. For both illumination schemes (directional [0°] and diffused), the output


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illumination intensities are also controlled digitally. See Table 1 for the comparison of the two distinct modes of illumination conditions.

Table 1. Chromatic and geometric viewing of a partially weathered sample. Note the difference in the ability to detect defects. The current VIEEW system is a desktop unit as shown in Figure. 4. As part of an inspection system, the VIEEW is equipped in order to permit repeatability and reproducibility. The viewing condition of each capture session is automatically recorded for optimum repeatability. The variable intensity control of the VIEEW system enables a wide variety of surface conditions to be viewed. Similarly, the position of the sample is recorded using a stepper motor controlled X-Y stage. This allows imaging the same location of the specimen as a function of exposure time.

Figure 4. The VIEEW System.


213 VIEEW Image Capture/Image Processing/Analysis System - Software


The image analysis software deals with specific defect types. In dealing with each defect, the program needs to decide what attributes are relevant and how they can best be measured. Some deal with the estimation of size, shape and distribution characteristics while others derive first order as well as second order surface texture properties to estimate damage. The first category, by its nature, requires a binary image as input, thus requiring a thresholding step to convert the image to black and white. The thresholding method selected must be appropriate for the defects in question. The measurements made for each are described separately below when discussing each of the defect types. Coatings Systems and Defect Types 1. Scratch and Mar Defects Test: Scratch and mar resistance testing of automotive coatings is done routinely and used as the basis for comparison of a coating's mechanical performance. Traditionally, both (lubricated) wet and dry mar testing protocols have been used (8) to inflict scratch and mar damage similar to that encountered in the field. Wet mar, for example, occurs in car washing, which is generally considered the most significant contributor to this type of damage, and in buffing operations used during repair. Dry mar comes from a broad range of materials that can contact the coating such as clothing, keys, paper, building materials, blowing sand, bushes, etc. Various imaging techniques, including optical and atomic force microscopy, have been used to determine type and extent of damage. Marring of a commercial styrenated-acrylic/melamine automotive clearcoat was done to create six distinct levels of surface damage. Marring was accomplished using a test device that has a reciprocating motion with the arm moving. The arm is equipped with a block to which a felt pad is mounted. The surface of the panel is marred using a slurry of aluminum oxide in water and a polishing cloth pad (LECO Pan W). A polishing cloth was selected that (itself) did not damage the coating. Therefore, all of the damage was assumed to come from the grit slurry. The Daiei Rub Tester was found to be particularly useful for performing this test. Standard conditions for testing of automotive clearcoats are 500 gram weight, 10 cycles, and 320 grit aluminum oxide particles at a concentration of 0.1%. In order to generate six levels of damage we applied 10, 20, 30, 60, 75, and 100 cycles, keeping other parameters the same. Objectives: The main objective of the scratch and mar evaluation was to differentiate and quantify the surface condition according to the amount of damage. It was particularly interesting to see whether the image analysis would match human perception of the


214 amount of damage visually detectable. Five images per each cycle were taken. Only 3 images per cycle are shown below. The data reported in a later section reflect all 5 readings.


Image Acquisition Condition: 1. Illumination Type: Directional Illumination 2. Illumination Intensity: Reflectance View 3. Image Dimension: 0.5 " X 0.67 " 4. Image Size: 320 X 240 pixels 6. Sample Color: Black

Table 2. Scratch and mar defect of automotive topcoat


215 Approach:


The overall effect of marring can best be measured using the overall loss in the ability to reflect lightfromthe surface. While gloss measurements are aimed at deriving this property, the color of the underlying base coat affects the results somewhat. In addition, the uni-directional marks on the surface make gloss measurement difficult. With the VIEEW system, the 0° directional illumination scheme provides a better measure of the reflective properties of the surface. Furthermore, since we obtain an image of the surface, other textural attributes can easily be determined for the surface. Some of the measurement techniques are listed below. We begin by examining the mean (x) and standard deviation (s) of image intensities. Elementary probability suggests that an image generated by randomly sampling a discrete uniform distribution, U ( G , G ) has an expected intensity value of (Gmin G ) / 2 and a variance of [ ( G -G + 1)2 - 1]/12. Most 'natural' images have a distribution that approaches normality, although often exhibiting a distinct skew. Since the light is kept constant for all specimens, the relative shift in the image brightness is directly a result of the surface scratching. With increasing marring, the image brightness decreases as well as a reduction in the range of the gray scales occupied in the image as measured by the breadth (variance or standard deviation) of the histogram. These provide a measure similar to gloss but are more exact. Similar to gloss, these provide a bulk measure of change. m m

m a x

+

max

m a x

m

m

It would also be desirable to have a measure of surface 'roughness' based on intensity variation. One such measure for a digital image is the area of surface relief. G may be used as an altitude coordinate, i.e., the height of a column of G cubes, each having the dimensions one pixel by one pixel by one standard intensity level. We then define the gray level area of a digital image as equivalent to the total number of exposed faces in a landscape composed of gray level columns. Here, we are only concerned with lateral area, and may ignore the top face of each column. This quantity can be measured by comparing the intensities of pairs of edge-adjacent positions, that is, those sharing a side. The number of exposed faces on one side of a column depends on the difference, D, between the intensity of the current position, G y, and the intensity of the adjacent position, G x+i,y+j- We ty interested in non-negative differences, and stipulate that D = G - G x+i,y+j ^ G >= G x+i,y+j> and 0, otherwise. The area of relief, A R , is therefore the sum of the area of all sides of all columns. But A R is also a function of the number of position pairs, P, and hence image size. To remove size effects, this quantity is normalized by computing R » A R / P . Note that P depends on whether the image is bounded (i.e., has a perimeter) or unbounded (e.g., an inner subset of a bounded image). In an unbounded image, every column has 4 sides (P = 4XY), whereas in a rectangular bounded image the columns on the perimeter have less than 4 sides with adjacent positions, and P = 8 + 6[(X-2) + (Y-2)] + 4[(X-2)(Y-2)]. For the sake of simplicity, we refer to unbounded images in the following discussion. x

8 1 6 on

x?

x

A

v

=


x ? v

v

216 For the sake of illustration, let us consider aR for some idealized images. When D = 0 for all position pairs, i.e., the image is monochromatic or 'flat', aR is zero. The maximum possible relief area, aR = 127.5, occurs in a regular checkerboard pattern composed of alternating 0 and 255 intensities. For an image generated by randomly sampling a discrete uniform distribution, U(0, N-l), the average difference, G -G x+i,y+j 2 i f(*i). We are only interested in cases where this difference is nonnegative, which occurs about half the time for large N, p(G >= G +J +J) = (1 + l/N)/2. The average normalized relief of such an image is therefore E(aR) = £ [XJ (N - x[ )/N2 ], where i has the range[0, N-l]. Another similar measure will be to examine the total volume occupied by the gray scale intensities (25-26). x ? v

=

x


x

v

x

JV

Surface roughness may also be determined using the fractal dimension of the surface. Other features of the texture may be quantified using second order statistics such as co-occurrence (25-26). 2. Acid Etch Defects Test: Acid etch resistance testing of automotive Original Equipment Manufacturer (OEM) coatings is done regularly to determine hydrolytic stability at/near the surface. Certain types of atmospheric pollution (i.e., sulfur oxides, nitrogen oxides) in combination with water (i.e., dew, rain) can result in formation of acidic solutions/environments capable of chemical bond hydrolysis. The styrenated-acrylic/melamine clearcoat network used in this portion of the study has both ester and ether type linkages susceptible of hydrolysis under these conditions. Acid etch damage results in what appears to be random patterns of microscopic and macroscopic pitting or etching, often significantly altering the appearance. This testing provides an important tool for rating and ranking coatings according to hydrolytic stability. Flexible clearcoats selected for study were applied to 10" X 10" thermoplastic olefin(TPO) panels that had been coated with adhesion promoter and black asecoat. These panels were fixed to horizontal tables and exposed for 14 weeks in at Jacksonville, Florida. Panels were washed and rated every two weeks with the final rating after 14 weeks of exposure, Florida. Coating A shown in Table 3 is a commercially available polyester/melamine type IK clearcoat. Coatings B and C are experimental IK systems that contain polyester/melamine and polyester/silane, respectively. The conventional visual by comparison with known acid etch performance provided that type C is the best performer. Objectives: For the analysis, it was most reasonable to examine the extent of damage by etch marks. As seen below, the amount of damage can be either interpretedfromthe area covered by the marks or the severity of etching effect depth wise. In addition, the


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differences in each type damage observed as a function of coating chemistry, exposure time and conditions, are of keen interest.


Image Acquisition Condition: 1. Illumination Type: Directional Illumination 2. Illumination Intensity : Reflectance View 3. Image Dimension : 0.5 " X 0.67 " 4. Image Size : 320 X 240 pixels 5. Sample Color : Black

Table 3. Acid etching defect of automotive top coat Approach: This type of defect is best quantified using the size of the affected areas. Shape can also be quantified relatively easily. The algorithms for determining size and shape are well known (23-26). Since these algorithms require a binary image as input, the quality of the image and the reliability of the thresholding step required can critically affect the resulting data. The VIEEW system (shown in Figure 4), can easily help obtain high quality images required for further processing. In the resulting binary image, the etched areas will appear as black and the unaffected areas appear as white. The total area coverage provides an overall measure of the severity of the etching. More specific information on size and shape can be obtained using geometrical descriptors. These measures may be quite relevant in terms of the surface texture and the polymer system used. Note that the images shown in Table 3 contain different sized defects. For more information on the methods for determining size and shape, see references (23).


218 3. Weather Induced Cracking Test:


A model styrenated-acrylic/melamine system was subjected to accelerated weathering that included UY-VIS irradiation, condensing humidity, and thermal cycling as factors in the exposure cycle. This coating did not have a UV-screener (UVA) and hindered amine light stabilizer (HALS) package in order to monitor degradation of an UV unprotected network. Panel samples were obtained after 500, 1000, 1500, 2000, 3000, 4000 and 5000 hours of exposure. After the accelerated weathering test, the samples also underwent a series of physical tests leaving scratch type marks on the coating surface. These marks were digitally minimized using a low pass Fourier filter to recover its weathered appearance. Objectives: The ability to monitor the onset of surface morphology change would be the main interest in this series. In addition, the cracking needed to be quantified. Image Acquisition Condition: 1. Illumination Type: Directional Illumination 2. Illumination Intensity : Reflectance View 3. Image Dimension : 0.5 " X 0.67 " 4. Image Size : 320 X 240 pixels 5. Sample Color : Blue Metallic

Table 4. Weathering induced cracking defect of automotive coating



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Approach: As suggested by Martin and co-workers, thefrequencyand density of cracks are obviously important considerations (22). We recently proposed that crack length and orientation were also very important. Crack length is an indicator of the severity of cracking while orientation may reveal other physical or chemical attributes responsible for cracking behavior. In this context, perhaps the most significant hurdle is defining what constitutes a single crack; cracks are often not single entities and cross over


220 other cracks (see Table 4). We demonstrated that crack length and orientation can be measured reliably (29). However, for the present discussion, we only refer to the frequency and density of cracking as measured by the total crack area coverage. Specific crack attributes such as length and orientation are meaningful when the samples' chemistry and history are known.


In dealing with cracking defects, we also need to convert the image to binary. The algorithms for carrying out the thresholding cracking images are rather more elaborate than those used in the case of defects previously discussed. Here, the features (cracks) are small entities and differ from the background only slightly in their gray level intensities. Therefore, thresholding needs to be carried out locally. This was discussed recently in full (25)

4. Gravelometer Test Chip Defects Test: The gravelometer test specimens (automotive type clearcoat/basecoat) were created according to the Dutch industry standard similar to the SAE J400 protocol. These specimens were solely created to demonstrate and investigate the imaging/image analysis' ability to quantify defects of this type. The chemical composition of the coating system and the gravelometer specification are, therefore, not available. One coating system was tested with varying levels of the gravelometer induced damage. The sample numbers were assigned to each sample according to the visual assessment protocol. Objectives: The objective was to accurately measure the damaged area and rank according to the ascending damage amount. Image Acquisition Condition: 1. Illumination Type: Directional Illumination 2. Illumination Intensity : Reflectance View 3. Image Dimension : 0.5 " X 0.67 " 4. Image Size : 320 X 240 pixels 5. File Format: DIB 6. Sample color : Blue


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1

2

3

4

Table 5. Gravelometer test samples Approach: Chipping defects created by high speed impact of airborne gravel on a top coat can be imaged using the VIEEW s geometric viewing configuration. The resultant defects appear as depressions or areas of mass loss including both adhesive and cohesive failures. Note that in multi-layed automotive coatings damage often occurs at/near interfaces(i.e., adhesion failure between layers). When airborne gravel impacts the surface, chipping may occur wherein severity and formation of damage would be based on its mechanical properties. Consequently, the chipped area would loose its reflective quality enabling an accurate image capture by the VIEEW hardware. The analysis of chip resistance is similar to that of the acid etching. The image needs to be converted to binary to isolate the chipped areasfromthe background. Results and Data Presentation 1. Scratch and Mar Defects Mean intensity and variance are plotted concurrently in Figure 5 to show its significance. At the lower cycle, the images show a higher mean intensity indicating little or no damage to the top surface. Consequently, the wide range gray composition (i.e., broad gray histogram) created by marring is reflected in a high level of variance. Contrary to this, as the damage becomes more severe, the gray histogram shifts and its breadth is reduced as indicated by the low variance values. The subsequent low mean intensity also signifies a deeper and more severe marring effect.



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Figure 5. Mean intensity, variance vs. number of cycles. 2. Acid Etch Defects All three type of coatings show distinct variation in etch mark formation. Type A shows a dense and the most severe etch marks among the series. Type B and Type C show a somewhat similar level of severity; however, the etch forming characteristics differ greatly in etch frequency and average etch size. It is also notable that the type A has lower reflective ability as indicated by the darker background. This characterizes its lesser smooth surface condition among the three types. For the data presentation(Figure 6), the percent area covered by etch marks is compared with the average etch mark sizes. The severity of type A coating is clearly indicated by its high % area value. The differences in formation between type B and type C are also clearly shown by average size.

3. Weather Induced Cracking The overall effect of weather induced surface degradation can be detected by the reflection of incident light (as seen in the scratch and mar evaluation). As the exposure increases, the geometric images became darker indicating the topcoat's diminishing light reflecting quality. After 3000 hours of exposure, presence of mudcracking type damage greatly reduced its reflective ability, further characterizing abrupt changes on the surface. As the crack density increased, the images became darker illustrating denser crack formation.



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Figure 6. Percent area, average size vs. coating type.

The mean intensity clearly characterizes the coating performance in terms of the reflective property. The abrupt shift in the mean intensity also highlights the abrupt change on the surface. The abrupt change on the surface is also precisely monitored and quantified by the two measures: Mean intensity and % cracked area (Fig. 7). Also notable is the shrinking of error (mean intensity) bars during 3000, 4000 and 5000 intervals indicate uniform crack formation over the entire viewing area of the image. 4. Gravelometer Test Chip Defects For this type of defect, a particle type analysis would be most appropriate since frequency, size and distribution are of interest. However, given the generality of particle analysis, only the ranking of the specimens regarding chipped area is presented in Figure 8.

Comparisons to Conventional Measurement Techniques 1. Scratch and Mar Defects Conventionally, scratch and mar type defects can be evaluated via gloss measurement. Considering the high reflectance of the tested coatings system, 20° gloss readings were measured. Total of five readings per each cycle were taken and averaged. A direct comparison between VIEEW data and Gloss data is also shown in Figure 9. A correlation coefficient is presented in Figure 10.



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0

1000

2000

3000

4000

5000

6000

Exposure Length (Hrs)

Figure 7. Mean intensity, % area cracked vs. exposure length.

Figure 8. Percent area vs. specimen #.


225 Revolution 20° Std Dev

10 82.9 1.4

75 58.2 4.4

60 60.3 1.8

30 64.8 2.1

20 78.0 2.3

200

85 V I E E W (Mean Intensity) 20° Gloss

180 -

80 75

160

h70

w

o

ed 140

65 5

EW


C U JG C

60 «

D ^

Service Life Prediction of Organic Coatings - American Chemical Society

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