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Standardized Color Management System
BYK-Gardner GmbH, 2010
Automotive - Exterior: Surface quality / - Harmony: Uniform Color & Appearance /
Waviness Color Effect Gloss Mottling
Automotive - Exterior: Challenges -
Various substrates and coating technologies Body vs. Add-on parts - Online/off line painting
- / Horizontal vs. Vertical
Stable process to guarantee quality over time
Page 4, BYK-Gardner GmbH, BYK-mac Presentation
Standardized Quality Control Management is needed
• Different people have different views on what is acceptable:
Paint shop <> QC department <> QC Customer <> Supplier <>
• Weak color memory – no statistics possible! - • You cannot control what you can’t measure! • Predictability: What happens if I change something? • Reliability: Supplier quality needs to be compared against objective
criteria to determine PASS – FAIL -
Effect Coatings 80% of todays automotive finishes are effect coatings
80%
• Pearlescent coatings result in a more spectacular color effect: Color Flop
:
• Metallic coatings accentuate the curved profile: Light – Dark Flop
-
• Effect finishes with special glitter effect (XirallicsTM)
Photo: Courtesy of
Page 6, BYK-Gardner GmbH, BYK-mac Presentation
Color Systems for Automotive Exterior Applications
ΔE*
ΔE*CMC
ΔE‘DIN Optimized for effect finishes to guarantee best visual correlation
L* = 100
+a*
-a*
+b*
-b* Blue
Red
Green
Yellow L* = + 58,12 a* = + 30,41 b* = + 36,26
L* = 0
CIELAB - System: L*a*b*- Coordinates CIELAB - : L*a*b*-
ΔE* = √ (ΔL*)2 + (Δa*)2 + (Δb*)2
Δ = Sample - Standard - +
- + - +
Δ L*
Δ a*
Δ b* Sample
ΔE* ΔL*
Δb*
Δa* Standard
CIELAB - System: Color Difference ΔL*, Δa*, Δb* CIELAB - : ΔL*, Δa*, Δb*
L* = 100
+a*
-a*
+b*
-b* 270°
0°
180°
90° L* = + 58,12 C* = + 47,32 h° = 50°
L* = 0
h°
C*
CIELAB - System: L*C*h°- Coordinates CIELAB - : L*C*h°-
CIELAB - System: Chromatic – Non Chromatic CIELAB - : –
+ b*
- b*
+ a* - a* B
P
Δ C* Δ H*
Non-chromatic colors: C* < 10
Use L*a*b*
Chromatic colors: C* > 10
Use L*C*h°
Limitations of CIELAB System / CIELAB Measured values do not correlate with visual impression
• Visual acceptability is based on ellipses not circles: Tolerances for hue are tighter than for chroma
• Chromatic colors have larger tolerances than pastels or near neutrals
• Size and shape of ellipse changes dependent on the hue: Acceptable color differences vary from color to color Green has larger tolerances than dark blue
• Angular dependency of the acceptance values
All colors within one ellipse are perceived as the same color.
• :
•
• :
•
Limitations of CIELAB System / CIELAB Measured values do not correlate with visual impression
• Acceptable color differences for lighter shade colors are larger than for similar darker shades
• More chromatic colors have larger tolerances than pastels or neutrals
±Δ a*
Product Standard
Acceptable Match
Rectangular versus Elliptical Tolerances
±Δ b*
Visually Rejected Match
Color Systems for Automotive Exterior Applications
Improved visual agreement on solids
ΔE*
Improved visual agreement on metallics: ΔEDIN6175-2
Improved visual agreement on solids: ΔECMC + ΔE94
ΔECMC – Color Measurement Committee of The Society of Dyers and Colorists (UK): 1988
• Based on visual evaluation of textile samples
• Currently specified in the following standards:
- British Standard BS6923 - American AATCC Test Method 173 - ISO International Standard 105-J03
• Based on elliptical (not rectangular) spacing and ΔL*C*H* ΔL*C*H* • Corrects for chroma, hue and lightness dependent perception
ΔECMC – Color Difference Formula
H S c cS
lS L
• 3-dimensional ellipsoid with axes corresponding to hue, chroma and lightness 3
• Weighting factors (= semi-axis) SL, SC and SH are dependent on color of standard = SL, Sc SH
• Application factors l and c to modify the lengths of semi-axes I C
( )
2 1 2 ab
2 ab
2 : CMC
H C L E ⎥ ⎥ ⎦
⎤
⎢ ⎢ ⎣
⎡
⎠
⎞ ⎜ ⎜ ⎝
⎛ Δ +
⎠
⎞⎜ ⎜ ⎝
⎛ Δ +
⎠
⎞ ⎜ ⎜ ⎝
⎛ Δ = Δ
H C L c l S cS lS
ΔECMC – Color Difference Formula
dECMC (l:c) =
√ dL*
lSL ( )2
+( dC*ab
cSC )
2 + ) dH*ab
SH
2
(
Where SL = 0.040975 L1 Sc = 0.0638 C1 + 0.638 1 + 0.01765 L1 1 + 0.0121 C1
Unless L1 < 16 when SL = 0.511 And SH = SC (Tf + 1- f) where f = (C1)4 1/2
(C1)4 + 1900
( )T = 0.36 + 0.4*cos( h°1 + 35) unless h°1 is between 164 ° and 345 ° when:
T = 0.56 + 0.2*cos( h°1 + 168) where L1, C1 and h°1 relate to the standard
ΔECMC – Color Difference Formula / Better correlation to visual perception: Brilliant Yellow with ΔChroma / ΔHue
Chromatic colors have larger visual tolerances in chroma than in hue
Color Difference: dE*
Color Difference: dECMC
-4
-3
-2
-1
0
1
2
3
4
-4 -3 -2 -1 0 1 2 3 4
-4
-3
-2
-1
0
1
2
3
41
Standard; STANDARD 07 L*=84.25; a*=5.74; b*=96
45°
-dL*
+dL*+db*
-db*
+da*-da*
-4
-3
-2
-1
0
1
2
3
4
-4 -3 -2 -1 0 1 2 3 4
-4
-3
-2
-1
0
1
2
3
41
Standard; STANDARD 07 L*=84.25; a*=5.74; b*=96
45°
-dL*
+dL*+db*
-db*
+da*-da*
L* a* b* dL* da* db* dC* dH* Standard Yellow Yellow -H Yellow -C Yellow +C
dE*
3.18 2.92 3.43
dECMC
1.64 0.88 1.02
84.25 5.74 96.00 84.46 8.88 96.49 0.22 3.14 0.49 0.73 84.52 5.75 93.09 0.27 0.01 -2.91 -0.19 84.37 5.86 99.42 0.12 0.12 3.43 0.08
Page 19, BYK-Gardner GmbH, BYK-mac Presentation
ΔECMC – Color Difference Formula / Influence of ratio l : c / L:c• Ratio l:c allows for a weighting of lightness to chroma L:c
• Most common ratio: 2:1
Variation in lightness can be double compared to chroma variations
L*
C* H*
ratio 1:1
C*
H*
L*
ratio 2:1
ΔECMC – Color Difference Formula / Influence of ratio l : c / L:c
Ratio l : c = 1 : 1
Ratio l : c = 2 : 1
-1
-0,5
0
0,5
1
-1 -0,5 0 0,5 1
-2
-1,5
-1
-0,5
0
0,5
1
1,5
22
45°
-dL*
+dL*+db*
-db*
+da*- da*
-1
-0,5
0
0,5
1
-1 -0,5 0 0 ,5 1
-4
-3
-2
-1
0
1
2
3
42
45°
-dL*
+dL*+db*
-db*
+da*- da*
ΔECMC = 0,84
ΔECMC = 0,46
Page 21, BYK-Gardner GmbH, BYK-mac Presentation
ΔECMC – Color Difference Formula / Influence of Commercial Factor: cf
cf
• Commercial Factor (cf) determines the overall size of the ellipse (cf)
• cf sets the color tolerance: ΔECMC < cf PASScf ΔECMC > cf FAIL
L*
C*
H*
cf=1.0 L*
C* H*
cf=0.5
ΔECMC – Color Difference Formula / Influence of Commercial Factor: cf
cf = 1.0
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-2 -1,5 -1 -0,5 0 0,5 1 1,5 2
-4
-3
-2
-1
0
1
2
3
42
45°
-dL*
+dL*+db*
-db*
+da*- da*
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-2 -1,5 -1 -0,5 0 0,5 1 1,5 2
-4
-3
-2
-1
0
1
2
3
42
45°
-dL*
+dL*+db*
-db*
+da*- da*
cf = 1.5
cf = 0.5
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-2 -1,5 -1 -0,5 0 0,5 1 1,5 2
-2
-1,5
-1
-0,5
0
0,5
1
1,5
22
45°
-dL*
+dL*+db*
-db*
+da*- da*
ΔECMC – Color Difference Formula / Summary
• One tolerance for all colors: cf = size of the tolerance ellipse
cf =
• Tolerance is based on elliptical spacing Size and shape of tolerance ellipse
is calculated based on Standard location in the color space
ΔECMC – Color Difference Formula / Summary Better correlation to visual perception:
• Chromatic Colors: Larger visual tolerance ellipse ΔECMC smaller for chromatic colors than for achromatic colors
(ΔC* and ΔH* are weighted less) compared to Δ E*
Δ E* ΔECMC ΔC* ΔH*
• Light Colors: Larger visual tolerance ellipse for lightness ΔECMC smaller for light colors than for dark colors
(ΔL* is weighted less) compared to Δ E*
Δ E* ΔECMC (ΔL* )
• Visual acceptability is decreasing from Hue Chroma Lightness l:c:h = 2:1:1
l:c:h = 2:1:1
ΔECMC - Typical Tolerances
1 1 2 110°
1 1 2 75°
1 1 2
45°
1 1 2 25°
1 1 2 15°
-15°
cf c l
1 1 2
Achromatic + Chromatic +
Metallics
0.5 1 2 45°
Solids
ΔE94 - Color Difference Formula: 1995
• Based on visual evaluation of new sample sets – solid colors only
-• Currently published in the following CIE recommendation:
- CIE Technical Report 116: Industrial Colour Difference Evaluation
CIE- CIE
• Based on elliptical spacing and ΔL*C*H* ΔL*C*H*• Corrects only for chroma dependent perception
ΔE94 - Color Difference Formula /
dL*
kLSL
• Weighting factors SC and SH are dependent on chroma of standard
• Application factors kL, kC, kH are used to correct for variations in reference conditions:
- Illumination: D65 - Illumination intensity: 1000 lx - Background field: neutral grey - Viewing field: > 4° - Sample: uniform color - direct contact – color difference 1 - 5 CIELAB units
dH*ab
kHSH dE 94 =
√ ( )2
+( dC*ab
kCSC )
2 + )
2
(
SL = 1 SC = 1 + 0.045 C*ab SH = 1 + 0.015 C*ab
kL = kC = kH = 1
ΔECMC and ΔE94 Color Difference Formula/ Limitations
• Tolerance is based on ΔL*C*H* ΔL*C*H* • Color change due to viewing angle is not part of the
calculation
DIN 6175- Part 2: Tolerances for Automotive Paints - 2001 DIN 6175- Part 2: - 2001 • Developed Collaboratively by European OEM’s:
Used by VW, Audi, BMW, Mercedes, General Motors … OEM :
VW, Audi, BMW, Mercedes, General Motors … • Based on visual evaluation of metallic samples
• Good visual correlation • Uses weighting functions dependent on color of standard • Uses application factors to differentiate between different
requirements (= g-factors): – Batch approval – Production: car body + add-on parts, repair line
(=g- ) – – : + ,
ΔEDIN6175-2
DIN 6175- Part 2: Tolerances for Automotive Paints - 2001 DIN 6175- Part 2: - 2001
Non-chromatic:
⎪ ⎪ ⎩
⎪ ⎪ ⎨
⎧
= =
+ =
7 . 0 7 . 0
5 . 31 15 . 0 γ
b a L
S S
L S γ γ √
2 *
2 *
2 *
' ⎟ ⎟ ⎟
⎠
⎞
⎜ ⎜ ⎜
⎝
⎛ +
⎟ ⎟ ⎟
⎠
⎞
⎜ ⎜ ⎜
⎝
⎛ +
⎟ ⎟ ⎟
⎠
⎞
⎜ ⎜ ⎜
⎝
⎛
= γ
γ γ γ γ
b b a a L L S g
Δb
S g
Δa
S g
ΔL ΔE γ γ
Chromatic:
⎪ ⎪ ⎪
⎩
⎪ ⎪ ⎪
⎨
⎧
⎟ ⎟ ⎠ ⎞
⎜ ⎜ ⎝ ⎛
+ + =
⎟ ⎟ ⎠ ⎞
⎜ ⎜ ⎝ ⎛
+ =
+ =
γ γ γ
γ
γ γ
21 20 . 0 14 . 0 7 . 0 ; 7 . 0 max
42 35 0 48 0 7 0 max
5 . 31 15 . 0
L C S
L γ. C γ. ; . S
L S
γ
γ
γ
H
C
L
√ 2
* 2
* 2 *
' ⎟ ⎟
⎠
⎞
⎜ ⎜
⎝
⎛ + ⎟
⎟
⎠
⎞
⎜ ⎜
⎝
⎛ + ⎟
⎟
⎠
⎞
⎜ ⎜
⎝
⎛ =
γ
γ γ γ γ
H H C C L L S g ΔH
S g ΔC
γS g ΔL
ΔE γ
DIN 6175- Part 2: Chromatic – Non Chromatic DIN 6175- Part 2: –
*C
*L
10 18
27
non-chromatic
• Samples can differ from angle to angle • Master panel and samples can differ
Combined effective color difference: :
ΔE’eff (γ) = σ(γ) ΔE’ab(γ) + (1 - σ(γ)) ΔE’CH(γ) σ = f (C*; L*) Achromatic: σ = 1 Chromatic: σ = 0
27 and 10 or < ≥ L C
18 ≥ C
chromatic
DIN 6175- Part 2: Typical Tolerances DIN 6175- Part 2:
1.2
1.2
1.2
1.0
gH
1.8
1.8
1.8
1.0
gC
1.2
1.2
1.2
1.0
gb
1.2 2.0 Repair Line with gap
1.2 2.0 Repair Line
1.2 2.0 Paint Line Body
1.0 1.0 Paint Batch Approval
ga gL
Application Factors
3.0 ΔEP
1.5 ΔEP
1.0
1.0
ΔEeff
Tolerance
ΔEP
ΔEC
Companies using similar approach as DIN 6175 – Part 2 DIN 6175 – Part 2
US Plant in Georgia
Global specification Global specification
Global specification
Similar Approach as DIN 6175 – Part 2 D6175-Part 2
DIN 6175 - 2 dEGM
Weighting Factors S S
Calculated based on color values of standard
Calculated based on color values of standard = DIN 6175 - 2
=DIN6175-2
Application Factors g g
Batch Approval 1 / 1 / 1 / 1 / 1 Production: 2 / 1.2 / 1.2 / 1.8 / 1.2
Same as DIN 6175 - 2 DIN 6175-2
Color Difference ΔE’ Always combined calculation
ΔE’ab + ΔE’CH
Either ΔE’ab or ΔE’CH Angle dependent
Tolerance Batch Approval 1.0 1.4
ΔSE = delta Color and Effect
Tolerance Production 1.0 1.4 ΔSE = delta Color and Effect
BYK-mac Total Color Difference analysis BYK-mac
√ + + =
ΔEp15° 2 ΔEtotal
ΔEp25° 2 ΔEp45° 2 ΔEp75° 2 ΔEp110°2 + +
5
√ + + =
ΔS15°2
ΔStotal
ΔS45°2 ΔS75°
2 ΔG2 +
4
√ + = ΔEtotal2
ΔSE ΔStotal
2
Page 36, BYK-Gardner GmbH, BYK-mac Presentation
New BYK-mac Multi-angle Color and Flake Characterization
Multi-angle Color Measurement • Illumination: 45°• Detection: 6-angles 6
-15°, 15°, 25°, 45°, 75°, 110°
Sparkle Characterization • Direct illumination: 15°,75°,45°from
perpendicular • Camera detection: 0°
Graininess Characterization • Diffused illumination • Camera detection: 0°
Principles of Color Management System
• Figures and Facts instead of feelings
• One binding reference
• Binding and realistic tolerances
● Complete solution: BYK-mac – wave-scan – cloud-runner Comprehensive „Standard Management“
General & customer specific color, appearance, mottling scales &
Definition of tolerances and limits
Standardized measurement procedure: Organizer Easy to use „Data Analysis“
Traffic light function in QC reports QC
Test Report: Single Vehicle Harmony
Process control charts: Scorecard – Trend Charts -
New smart-chart Software smart-chart
NEW smart-chart Software for BYK-mac, wave-scan Family, cloud-runner
smart-chart Software: Standard Management /
Define tolerances and limits Define color families with common settings: ΔE equation, geometry, statistic
DE , ,
Set geometries
Set Color difference method: dEc -- dEp
dEc -- dEp
smart-chart Software: Standard Management /
Define effect tolerances / limits /
Set effect geometries
Color Measurement in Practice: Standard Management
Add-on parts
Production QC QC
Define the Master
Color Measurement in Practice
Alternative 1: Distribution of „Working Masters“ 1
Design Master
Visually accepted working masters Measured with
individual instruments
Color Measurement in Practice
Alternative 1: Distribution of „Working Masters“ 1
Design Master
Production of working Standards
Limitations:
Working standards differ from each other Inter-instrument agreement:
Excellent with BYK-mac due to LED technology LED BYK-macWorking
Standards for plants & suppliers
+ b*
- b*
+ a* - a* All plants and suppliers use the same „master-master“.
Color Measurement in Practice
Alternative 2: Physical „Master-Master“ Panel2
Color Measurement in Practice: Standard Management
How is the „Master-Master“ determined?
• „Master-Master“ is the panel closest to the average of all measured paint masters (~ 200)
“
Each plant and supplier must measure „master-master“ of each color with individual instrument
☺ Future color difference measurements are based on one common
reference value
-1.5 -1
-0.5 0
0.5 1
1.5
-1 -0.5 0 0.5 1
Color Measurement in Practice: Standard Management
Alternative 2: Physical „Master-Master“ Panel 2
Limitations: Working standards differ from each other
Inter-instrument agreement
Global supply chain
Design Master
Production of Working Standards
“Master Master” standard is determined
Working Standards for visual control
“Master Master” is measured with every
BYK-mac BYK-mac
Color Measurement in Practice: Standard Management
Alternative 3: Digital Standard with BYK-mac 3 BYK-mac
“Master Master” is measured with
Master BYK-mac BYK-mac
Digital Master is emailed to supply
chain
No more limitations:
One global reference
Design Master
Production of Working Standards
“Master Master” standard is determined
Working Standards for visual control
BYK-mac makes Digital Master possible BYK-mac Excellent inter-instrument agreement
100
0
L*
50
green beige black metallic white yellow green bright silver bright red solid blue dark red steel gray metallic dark silver green yellow yellow blue violet metallic
14 Colors 146 panels/color w/ 6 readings/panel
6 62 BYK-mac 2 BYK-mac
Test performed manually – Operator Influence -
BYK-mac inter-instrument agreement BYK-mac Delta – Delta comparison: 15° and 25°angle
- 15° 25° ΔL* Δb* Δa*
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-5 -3 -1 1 3 5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-5 -3 -1 1 3 5
Δ BYK-mac
Δ -
BYK-
mac
1- Δ
BYK
-mac
2
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
15°
25°
BYK-mac inter-instrument agreement BYK-macDelta – Delta comparison: 45° angle
- 45°
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-5 -3 -1 1 3 5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-macΔ
BYK
-mac
1 - Δ
BYK
-mac
2-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
ΔL* Δb* Δa* 45°
BYK-mac inter-instrument agreement BYK-macDelta – Delta comparison: 75° and 110° angle
- 75° 110°
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-5 -3 -1 1 3 5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac - Δ
BYK
-mac
2-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
ΔL* Δb* Δa*
-2
-1,5
-1
-0,5
0
0,5
1
1,5
2
-5 -3 -1 1 3 5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
-1
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
-2,5 -1,5 -0,5 0,5 1,5 2,5
Δ BYK-mac
Δ B
YK-m
ac1
- Δ B
YK-m
ac2
75°
110°
Key for standardized color managment
smart-chart Software: Digital Standard smart-chart
smart-chart Software: Standard Management for wave-scan smart-chart
• Define scales to be displayed
• Define limits for Pass / Fail
/
NEW smart-chart Software for BYK-mac, wave-scan Family, cloud-runner
smart-chart Software: Organizer/
Clear sample identification:
Par 1: Models Par 2: Colors Par 3: Paint Booths
smart-chart Software: Organizer for BYK-mac smart-chart BYK-mac
Menu guided operation:
Car schematics help to define sampling procedure
smart-chart Software: Organizer for BYK-mac Example: Color Harmony test procedure
• Checkzone creation
• Curvature per checkzone
• Number of readings per checkzone
• Definition of “Panel Matches”
• Measurement Direction
BYK-mac Reliable Operation and Handling
• Stable positioning due to 4 trigger pins on bottom plate 4
• Sensitivity of pins can be adjusted to sample curvature
• Curvature > 500 mm >500mm • Measurement of sample temperature
Symbol Sample Curvature Example
I Flat Test Panel 4 Pins < 0.1 mm ) Low curvature Hood 3 Pins < 0.1 mm; 1 Pin < 0.3 mm O Medium curvature Bumper 3 Pins < 0.3 mm; 1 Pin < 0.9 mm o High curvature Mirror Housing 3 Pins < 0.6 mm; 1 Pin off
Off Pins deactivated, but it is ensured that no ambient light will enter aperture
Color Measurement in Practice
Reproducible Production QC
Defined measurement areas and measurement direction
1 2
8
3
5
4
6
7
Direction of instrument illumination
smart-chart Software: Organizer for wave-scan
• Checkzone creation
• Scan length per checkzone
• Number of readings per checkzone
• Definition of “Groups”
NEW smart-chart Software for BYK-mac, wave-scan Family, cloud-runner
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smart-chart Software: Data Analysis - List -
• Filter database by:
Status – Date – Model – Color – Paintline – Instrument
- - - - -• Click on “Refresh”
smart-chart Software: Data Analysis – Test Report - Single Vehicle Harmony “Data Table”
• Match to standard with Pass/Fail /• Panel match with Pass/ Fail analysis
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Page 66 - Seminar Material 2010
smart-chart Software: Data Analysis – Test Report - Single Vehicle Harmony “Chart”
Page 67 - Seminar Material 2010
smart-chart Software: Data Analysis – Scorecard - Management Summary
Page 68 - Seminar Material 2010
smart-chart Software: Data Analysis – Trend - Production / Batch Process Control
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Page 69 - Seminar Material 2010
smart-chart Software: Data Analysis – Trend Comparison - Production vs Batch or Body vs Add-on Parts
NEW smart-chart Software Standardized QC management system
Thank you for your attention