DCC Sparkle and Graininess Tolerancing Study - … Dec2016 Sparkle Tolerancing Study.pdf · DCC Sparkle and Graininess Tolerancing Study presented at BYK-Gardner User ... DCC Color

DCC Sparkle and Graininess Tolerancing Study presented at BYK-Gardner User Meeting, October 26, 2016 Larry Steenhoek, Jeff Alspach, Allan Rodrigues

Current work on Color Difference Equations

DCC Color Education Course

2AXALTA COATING SYSTEMS PROPRIETARY

DCC Sparkle & Graininess Study

Presentation Outline

• DCC Committee Purpose and Project Background

• Experimental and Data Analysis Procedures

• Sparkle Study and Results

• Graininess Study and Results

• Findings and Future Work

• Acknowledgements


March 2013 Sub-committee Meeting Attendees

Committee Purpose and Membership

Purpose: Upgrade SAEJ1545 with the goal of standardizing automotive industry practices for establishing color and flake appearance measurement and methodology for setting meaningful tolerances.

Membership:

Chairman: Jeff Alspach, Axalta, Mt. Clemens, MI

Car manufacturers: Audi, Ford, GM(need others)

Coatings Suppliers: AkzoNobel, Axalta, BASF, PPG

Instrument Manufacturers: BYK-Gardner, X-Rite, GTI

Includes members from ASTM, CIE, DIN


Project Background

The BYK-mac multi-angle spectrophotometer is applied in measuring the color and flake appearance differences of automotive paints.

Overall purpose: Determine tolerance threshold for sparkle difference

Determine tolerance threshold for graininess difference

Determine inter-company differences: Do observers from a variety of companies agree with initial observations taken at Axalta?

Through industry participation, educate and raise awareness of spatial texture.

Process: Estimate sparkle and graininess difference tolerances for several colors by visual assessment, analyzing with “Binary Logistic Regression”.


BYK-mac Geometry

Courtesy of BYK-Gardner, GmbH


Basic Equations and Terms

Used DE94 color differences with the gonioapparent SL Lightness correction:

SL = 0.034L*; If L* ≤ 29.4., SL = 1.0

Sparkle difference dS and graininess difference dG as provided by the BYK-mac.

Definitions (ASTM E284):

Sparkle, n- The aspect of the appearance of a material that seems to emit or reveal tiny bright points of light that are strikingly brighter than their immediate surround and are made more apparent when a minimum of one of the contributors (observer, specimen, light source) is moved.

DISCUSSION—Sparkle is perceived under intense directional illumination only.

Graininess, n- for gonioapparent coatings, the perceived contrast of the light/dark irregular pattern exhibited when viewed under diffuse illumination, scale typically >100 micrometers.

DISCUSSION—Also referred to as diffuse coarseness.


Experimental Procedures

• The panels are observed in the BYKO-Spectra Effect lightbooth.

• The viewing window on the lightbooth is shortened from 20 in. width to 5 in. width (helps focus on the center of the panels)



• At least 30 observers were asked to make visual assessments of sparkle or graininess difference acceptability. All of the observers had experience in judging automotive color and appearance acceptability. (Note: 30 observers were from Axalta, additional observers from several companies, hosted by Thierry).

• Panel pairs were randomly presented.

• Panels supporting board set at 45 degree, allowing viewing perpendicular to the panels with the sparkle light at 15, 45 or 75 degrees. The light intensity is adjusted to 7 (1 to 10 scale).



Following is an example of the process used in selecting sample pairs for sparkle visual assessments:

Used pairs of panels with known dE94 and dS measured by BYK-mac at the appropriate angle

dE94 < 1

Remaining panels

dS < 1.3 (assumes 1.3 close to 100% rejection)

Remaining panels

Choose pairs evenly spaced for:

0.30< ds <1.30, dE94 < 0.85

Remaining pairs used

(Added dS pairs close to expected high and low rejection)



Observers were asked:

“Ignoring any color differences, would you accept this sparkle (or graininess) difference between two adjacent car parts on your car?”

Accept, “YES”

Reject, “NO”


Observer Data Smoothing

This process compensates for subjective variation in each observer’s assessment

Berns et al, Visual Determination of Suprathreshold Color-Difference Tolerances Using Probit Analysis. Color Res Appl 1991; 16:297-316

dSOriginal

ResponseTransform Sum of 3

IntegerDivide by

2

SmoothedResponse

Add “0” 0

1.48 Yes 0 0 0 Yes

1.57 Yes 0 1 0 Yes

1.60 No 1 1 0 Yes

1.75 Yes 0 2 1 No

1.84 No 1 2 1 No

Add “1” 1


Binary Logistic Regression - Basics

Threshold Value at 50% Acceptance

T50=177

Goodness of Fit TestsTest DF Chi-Square P-ValueDeviance 233 206.34 0.895Pearson 233 285.85 0.010Hosmer-Lemeshow 3 12.04 0.007

Odds Ratios for Continuous PredictorsUnit of Change Odds Ratio

Sg 0.1 1.58


Typical Visual Assessment Results

Std ID Bch ID dE94 15 OK Rej Rej Freq 15 ds

4 5 0.17 43 4 0.09 0.31

2 11 0.25 42 5 0.11 0.41

9 10 0.26 36 11 0.23 0.53

3 4 0.18 36 11 0.23 0.99

2 3 0.22 30 17 0.36 1.10

8 10 0.54 18 29 0.62 1.15

3 11 0.46 18 29 0.62 1.23

6 10 0.83 12 35 0.74 1.47

5 9 0.74 11 36 0.77 1.65

T50=1.15

A 50% frequency of rejection is the recommended tolerance

Test DF Chi-Square P-Value

Deviance 421 465.95 0.064Pearson 421 427.13 0.408Hosmer-Lemeshow 7 13.08 0.070

Unit of Change Odds RatioSg 0.1 1.31


Binary Logistic Regression Analysis

T50=1.43

Test DF Chi-Square P-Value

Deviance 293 312.75 0.204

Pearson 293 290.92 0.523

Hosmer-Lemeshow 6 8.44 0.208

Unit of Change Odds Ratio

Sg 0.1 1.32


Summary of Sparkle Results

Color CenterAppearance Parameter

T50 L* C*

Black dS15 (Axalta) 1.76 18.61 2.87

dS15 (Thierry) 1.78 18.61 2.87

dS15 (Combined) 1.77 18.61 2.87

dS45 (Combined) 1.43 5.04 0.60

dS75 (Axalta) 0.65 2.71 0.51

dS75 (Thierry) 0.54 2.71 0.51

dS75 (Combined) 0.60 2.71 0.51

Bright Yellow dS15 (Axalta) 1.18 77.79 59.75

dS15 (Thierry) 1.12 77.79 59.75

dS15 (Combined) 1.15 77.79 59.75

Cyber Gray dS45 (Axalta) 0.71 18.21 1.73

dS75 (Axalta) 1.03 7.48 1.56

Blue #9 dS15 (Axalta) 1.73 51.23 55.26

020

0460

.50

0.1

0

57

50

25

00

5.1

dlohserhT

*L

*C

D Scatterplot of Thr3 shold vs L* vs C*e

T50

3D Scatterplot of T50 vs L* vs C*


Graininess Study

Graininess: Visual texture observed under cloudy day with diffused illumination

High Graininess Low Graininess

Images Courtesy of BYK-Gardner, GmbH


Graininess Study

BYKO-Spectra Effect lightbooth: Color evaluation source at 45.

Light diffusion was enhanced with frosted plastic over light source

T50 = 0.54T50 = 1.31


Summary of Studies To Date

NO = Color difference between available panels too large to accurately judge ds or dG

? = May be possible, no observations to-date

* Bright Yellow has too much scattering pigment to observe graininess or sparkle at other angles

ColorCenter

ds15 ds45 ds75 dGNumber of Observers

Black 30+17

Cyber Gray NO NO 31+17

Brt Yellow* NO NO NO 30+17

Blue #9 ? ? ? 28

Blue #14 ? ? ? 30

CompanyNumber of Observers

Axalta 30+3

Byk 3

Konica Minolta 1

Toyal 1

GM 2

BASF 1

Celanese 1

Keystone Aniline 1

Abedmego Environmental 2

Bosch 1

Independent Consultant 1

Total 47

Participants


Findings

Acceptability tolerance for sparkle differences were determined for 4 colors at 15, 45, 75 degree viewing.

Observations by different groups of observers (different companies, OEMs, suppliers, etc.) were all within the predicted confidence intervals.

Some colors did not exhibit sparkle at all angles, e.g., light scatter within Bright Yellow suppresses sparkle at viewing angles greater than 15 degrees.

Some sparkle was visible when assessing graininess with the current BYK viewer, resulting in observer confusion. An additional diffuser for suppressing the sparkle worked well for graininess difference observations in this study.

Sparkle and graininess differences are difficult to assess when obvious color differences are also observed. We limited color differences between panel pairs to DE94 less than 1.0. It is very difficult to create panel sets meeting these constraints.


Findings (Cont.)

Due to the fact visual color harmony audits are done under a variety of lighting conditions, the differences observed in our study (under controlled conditions in a light booth) might be masked or magnified in an audit.

Achieving a good correlation of visual and instrumental differences for color and spatial appearance differences can help deliver reasonable tolerances.

Over controlling instrumental assessment and under controlling visual assessments or vice versa will hinder implementation of instrumental control.

Sparkle and graininess acceptability varied by color and angle of view/measurement. Therefore tolerances need to be set accordingly.


Future Work

• Additional visual assessments for additional sparkle angles and other metallic colors to estimate the sparkle and graininess difference tolerances.

• Explore generalized tolerances, e.g., possible relationship to color, lightness, hue, chroma, contrast, absorption vs. scattering pigmentation, etc.

• Observers often found it difficult to ignore color difference when judging sparkle or graininess differences, suggesting that assessments of color/sparkle/graininess differences are not independent of these individual components. Need industry agreement to standardize assessment when these differences are observed in combination.


Overall Progress and needs on Specification of GonioapparentColor & Appearance

Spatial Appearance Definitions in ASTM E284 (Standard Terminology of Appearance)

? ASTM standard on visual assessment of spatial appearance

? ASTM standard on measurement of spatial appearance

? Revision of SAE J1545 (Standard for instrumental color difference measurement for exterior finishes, textiles, and colored trim) and J361 (Visual evaluation of interior and exterior automotive trim) to address sparkle and graininess

Note: Standards organizations are reluctant to standardize around instruments supplied by only one manufacturer. Can spatial appearance assessment be addressed in a generic fashion?


Acknowledgements

BYK-Gardner for their support and providing the BYKO-Spectra Effect lightbooth for the visual assessments

Members of the DCC Committee

DCC for their sponsorship

Our colleagues in Axalta Coating Systems for their inputs and participation in visual assessments

Thierry Corporation for hosting observers in collecting additional data.

Participants from automotive companies and suppliers in on-going experiments

AXALTA COATING SYSTEMS

Any Questions?

Current Work on Color Difference Equations


Uniform Color Scales CIELAB or CIE76

222 *** baLE DDDD222 *** HCLE DDDD

2*2** baC

*)/*(tan 1 abh

222 **** CLEH DDDD

h = hue angleDH = metric hue difference

This system is more consistent withhow we perceive color


CIE94 and CMC Equations

General Form of the Color Difference Equation

DE DL*

KL

SL

2

DC

ab*

KC

SC

2

DH

ab*

KH

SH

2

0.5

CIE94 Equation CR&A, 18, 137-139(1993)

For solid colors: SL = 1.0

For metallics: (not in CIE94

recommendation)

SL = 0.034L*; If L* <= 29.4, SL = 1.0

SC = 1 + 0.045C*ab

where C*ab is that of the standard

SH = 1 + 0.015C*ab

The parametric factors KL:KC:KH = 1:1:1

are generally satisfactory in CIE94

CMC typically uses 2:1:1

The CMC Equations

For L>16, SL

0.040975L*

10.01765L*

For L<=16, SL = 0.511

SC

0.0638Cab

*

10.0131Cab*

0.638

SH = (FT + 1 –F) SC

where

F (Cab* )4

(Cab*

)41900

0.5

T = 0.36 + abs[0.4 cos(35 + hab)] unless h is between 164˚ and 345˚ then

T = 0.56 + abs[0.2 cos(168 + hab)]

D

D

D

D

DD

HH

ab

CC

abT

HH

ab

CC

ab

LL SK

H

SK

CR

SK

H

SK

C

SK

LE

*****222

2

2

50*20

50*015.01

L

LSL

-60

-40

-20

0

20

40

60

80

100

120

-60 -40 -20 0 20 40 60 80 100 120

a*

b*

CIEDE2000


Lightness Weighting Factor SL

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

0 20 40 60 80 100 120

L*

SL

CIE 2000

CMC(1:1)

CMC(2:1)

E12.12


AUDI 2000

ddE combined

dE AUDI 2000 CIE dE 2000

Suggested Next Step

Where fi are defined separately for L, C, H for solid or gonioapparent colors

Lex, K. & Kiggle-Bockler, Combined Color difference Method fo Multi-Angle ApplicationBYK-Gardner User Meeting, 2016

DCC Education Activity


DCC Course: Matching & Control of Metallic and Pearl Colors

Presentations by experts from different coatings companies and instrument manufacturers

Hand-on exercises reinforcing concepts, and use of spectrophotometers

Visual Match Evaluation and Colorimetry (Allan Rodrigues)

- Components of seeing color that lead to colorimetric equations

- Consistent color match terminology

- Multi-angle viewing of gonioapparent materials

- Visual exercises to reinforce understanding these concepts.

Effect Pigments for Automotive Topcoats (Claudia Royal, Axalta Coating Systems)

- Characteristics of effect pigments leading to their use

- Types of effect pigments: aluminum, mica, synthetics, multi-layer, glass, non-flake (micronized TiO2, Graphite)

- Guidelines for durable and reproducible color formulation

- Visual examples of these flakes in finishes


DCC Course (contd.)

Impact of the Application Process on Color in Metallic/Pearl Coatings (Chris Fowler, BASF)

- Appearance properties we are looking for (gloss, DOI, no mottle, sag, craters, etc)

- Factors affecting appearance (surface roughness, coatings formulation, rheology, application)

- Application sequences (spray, flash, bake, etc), booth environment, equipment types

- Spray processes (conventional, HVLP, rotational, variables, limitations of each process)

Colorimetry Advances and Measurement of Gonioapparent Colors (Allan Rodrigues)

- Improvements on CIELAB

- Multiple angle viewing and colorimetry

- Flake characterization (sparkle, graininess) and measurement

- Setting tolerances

General Discussion (Student inputs, standards committees, DCC activities)


Other Color Courses

Eastern Michigan University Short Course (Kendall Scott)

Instrument manufacturers provide courses

Universities provide degrees in color science as well as short 1-week courses (e.g., RIT)

Inputs on courses or 1-day workshops DCC should provide

- Paint vs. plastics color

- Exclusively on rheology and application

- Textiles – leather, thread, carpet, fabric

- How to match Bumper/Body/Parts.

- Application based class, WBBC vs. SBBC

- Matching European colors to North American colors

- Your inputs???

AXALTA COATING SYSTEMS

Thank you

Any Questions?


CIE DE2000

DE00 DL'

kLSL

2

DC'

kCSC

2

DH'

kHSH

2

RT

DC'

kCSC

DH'

kHSH

12

G 0.5 1C ab

* 7

C ab* 7

257

L’ = L* a” = a*(1+G) b’ = b*

SL 10.015 L '50

2

20 L '50 2

SC 10.045C '

TCSH '015.01 T 1 0.17cos h '30 0.24 cos 2h ' 0.32cos 3h '6 0.20cos 4h '63

RT sin 2D RCD 30exp h '275 25

2

RC 2C '7

C '725

7


AUDI2000


Audi2000 for C* < = 10


Combined Color and Appearance Equations

CIECAM02 was developed for color imaging systems.Some use it as a color difference formula• It is the color appearance model by CIE TC8-01 (Color Appearance Modelling for

Color Management Systems)

• The model consists of:- A chromatic adaptation transform, CIECAT02 and- Equations for technically defined dimensions of color appearance: brightness (luminance), lightness, colorfulness, chroma, saturation, and hue.

• CIECAM02 inputs are the tristimulus values of the stimulus, the tristimulus values of an adapting white point, adapting background, and surround luminance information, and whether or not observers are discounting the illuminant.

Reference: Fairchild MD, Color Appearance Models: CIECAM02 and Beyond, IS&T/SID 12th Color Imaging Conference, Tutorial T1A, 11/9/04.

https://en.wikipedia.org/wiki/Color_appearance_model

https://en.wikipedia.org/wiki/Tristimulus_value

Documents

DCC Sparkle and Graininess Tolerancing Study - … Dec2016 Sparkle Tolerancing Study.pdf · DCC Sparkle and Graininess Tolerancing Study presented at BYK-Gardner User ... DCC Color