Non Skid Coating Formulation Utilizing a Design of Experiments (DOE)

Approach

TRFA Annual Meeting, Fort Lauderdale FL14 November 2005Charles S. Tricou

Applied Research LaboratoryThe Pennsylvania State University

Repair and Replacement

• Repair is time-, material-, and labor-intensive.

• Repair costs Range from $13- $25 /ft2

– CV 63 (November 2000)» 116,000 ft2

» Labor: $22.50 / ft2

» Material: $ 2.80 / ft2

– CVN 72 (April 2004)» 70,000 ft2

» Cost: $1.4 Million ($20 / ft2 )

Durability• Approximately 80% of CVN flight deck nonskid coatings

are replaced following each deployment. Extending the durability and functionality of nonskid coatings to last through 2 full deployments will save the Navy ~ $5M per year.

• Nonskid coatings in arrested landing areas are removed and replaced 2 or 3 times per deployment cycle.

• Flight deck coatings have degraded during deployment to an extent necessitating repair. Repairs at foreign ports are very expensive and result in temporary loss of platform availability.

Overview

Approach

Develop a High-Performance Epoxy / Urethane Polymer

• A design of experiments (DOE) approach was used to optimize coating performance in corrosion resistance, chemical resistance, impact resistance, and long-term coefficient of friction (COF) retention.

• This approach offers the potential of achieving maximum performance from an organic-based nonskid coating. After qualification, such a system may be used as a drop-in replacement for current epoxy-based systems.

Performance Measurements (Outputs)

Coating performance measurements Adhesion

Corrosion (QUV, Salt Fog, Immersion, etc.)

Service-specific durability tests• Erosion / Wear

• Impact Resistance

• Chemical Resistance

Performance Measurements (Outputs)

Coating performance measurements Adhesion

Corrosion (QUV, Salt Fog, Immersion, etc.)

Service-specific durability tests• Erosion / Wear

• Impact Resistance

• Chemical Resistance

DOE Approach – What is it?

Design of Experiments (DOE) is a scientific approach to experimentation. A good DOE will yield the following benefits:

Aid in the selection and isolation of the important variables to be studied

Minimize the number of experiments that must be carried out to yield meaningful results

Maximize the amount of information that can be extracted from the experiments

Minimize the cost of product development and process control

DOE – How it Works2-Factor (full factorial) Linear

Linear Design 2 levels for each factor 2n trials For 2 factors n = 2

→ 4 trials required

Factor 1

Fac

tor

2

Provides information aboutinteractions between factors (variables)

2-Factor (full factorial) Quadratic

Factor 1

Fac

tor

2

Non-Linear Design 3 levels for each factor 3n trials For 2 factors (n = 2)

→ 9 trials required

3-Factor (full factorial) Linear

Factor 1

Factor 2Linear Design 2 levels for each factor 2n trials For 3 factors n = 3

→ 23 trials required

Factor 3

Mixture Designs

Constraints C1 + C2 + C3 = Fixed % Component 1

Component 3Component 2

Binary Blend

Non Skid Polymer FormulationComponents & Levels

Components (Levels)A. Polyamine Curing Agent #1 (Stoich)B. Polyamine Curing Agent #2 (Stoich)C. Modifier #1 (0% – 30% by weight of base resin)D. Modifier #2 (0% – 30% by weight of base resin)E. Modifier #3 (0% – 30% by weight of base resin)F. Adhesion Promoter #1 (0% – 0.5% by weight of Resin)G. Adhesion Promoter #2 (0% – 0.5% by weight of Resin)H. Base Resin (100 grams)

Constraints: Total Modifier cannot exceed 30%0 ≤ C + D + E ≤ 30 grams

Design Strategy

In total, there are 8 potential components that may be used in the coating formulation. However, the amount of base resin used in each trial is held constant at 100 grams. Since the amount of resin does not vary, the base resin may be eliminated as a variable, reducing the number of variables to 7.

To maintain stoichiometry, the amount of one curing agent used will depend upon the amount of the other curing agent used. By expressing the amount of one of the curing agents as a fraction of the total curing agent used, the other curing agent is eliminated as a variable, reducing the total number of variables from 7 to 6.

Design Strategy

A quadratic D-Optimal design was chosen for this experiment. The D-Optimal design provides substantial information with a a minimum number of trials.

Components (Levels)A. Polyamine Curing Agent #1 (Fraction of total curing agent used: 0 - 1)B. Polyamine Curing Agent #2 (Stoich, based on amount of PCA1)C. Modifier #1 (0% – 30% by weigh of Resin)D. Modifier #2 (0% – 30% by weight of Resin)E. Modifier #3 (0% – 30% by weight of Resin)F. Adhesion Promoter #1 (0% – 0.5% by weight of Resin)G. Adhesion Promoter #2 (0% – 0.5% by weight of Resin)H. Base Resin (100 grams)

D-Optimal Design: 38 Total Trials Run

Curing Agent 1

MOD 1 MOD 2 MOD 3 AP 1 AP 2

1 0.00 0.0 15 0 0.5 02 1.00 0.0 30 0 0 0.53 1.00 0.0 0 0 0.5 04 1.00 0.0 30 0 0.25 05 0.00 0.0 0 30 0 0.56 0.50 0.0 0 0 0 0.57 0.00 0.0 30 0 0.5 0.58 1.00 30.0 0 0 0 09 0.00 30.0 0 0 0.5 0.2510 0.00 0.0 0 0 0 011 1.00 0.0 0 30 0 0.2512 0.00 0.0 15 15 0 013 0.25 3.8 3.75 18.75 0.25 0.12514 0.00 0.0 0 30 0.5 015 0.00 0.0 0 0 0 016 1.00 0.0 15 0 0 017 1.00 15.0 0 15 0.5 018 0.00 15.0 15 0 0.5 019 1.00 15.0 0 0 0.5 020 0.00 0.0 15 15 0 021 0.00 30.0 0 0 0 022 0.00 0.0 30 0 0 0.523 1.00 30.0 0 0 0.5 0.524 0.00 0.0 0 30 0.5 0.525 1.00 0.0 0 15 0 0.526 0.50 10.0 10 0 0.25 0.2527 1.00 0.0 0 0 0.5 028 1.00 0.0 0 0 0.25 0.529 0.00 0.0 0 0 0.5 0.530 1.00 0.0 30 0 0.5 0.2531 1.00 15.0 0 15 0 0.532 0.00 0.0 0 0 0.5 0.533 0.50 0.0 0 30 0 034 1.00 0.0 0 15 0 0.535 0.00 30.0 0 0 0 0.536 1.00 0.0 0 30 0.5 037 0.00 0.0 30 0 0 038 1.00 0.0 0 30 0.5 0.5

Component Polyamine Curing Agent

1

Polyamine Curing Agent

2

MODIFIER 1

MODIFIER 2

MODIFIER 3

ADHESION PROMOTER

1

ADHESION PROMOTER

2

Resin (grams)

Total Mixture (grams)

Fraction of Available Epoxide Equivalents

0.00 1.00 0.00 15.00 0.00 0.50 0.00 100 200.00

Equivalents 0.00 0.44 0.00 0.06 0.00 0.0021 0.50 200.00grams 0.00 52.83 0.00 15.00 0.00 0.50 0.00 100 168.33

% Total 0.00 0.31 0.00 0.09 0.00 0.00 0.00 0.59 1.00

Conversions

Trial #1

Experimental Design Run

Curing Agent 1 (grams)

Curing Agent 2

(grams)

MOD 1 (grams)

MOD 2 (grams)

MOD 3 (grams)

AP 1 (grams)

AP 2 (grams)

Resin (grams)

Total Mixture (grams)

1 0.00 52.83 0.00 15.00 0.00 0.50 0.00 100.00 168.332 66.19 0.00 0.00 30.00 0.00 0.00 0.50 100.00 196.693 86.62 0.00 0.00 0.00 0.00 0.50 0.00 100.00 187.124 66.37 0.00 0.00 30.00 0.00 0.25 0.00 100.00 196.625 0.00 67.43 0.00 0.00 30.00 0.00 0.50 100.00 197.936 43.13 29.75 0.00 0.00 0.00 0.00 0.50 100.00 173.387 0.00 45.91 0.00 30.00 0.00 0.50 0.50 100.00 176.918 65.63 0.00 30.00 0.00 0.00 0.00 0.00 100.00 195.639 0.00 45.53 30.00 0.00 0.00 0.50 0.25 100.00 176.2810 0.00 59.50 0.00 0.00 0.00 0.00 0.00 100.00 159.5011 97.75 0.00 0.00 0.00 30.00 0.00 0.25 100.00 228.0012 0.00 56.55 0.00 15.00 15.00 0.00 0.00 100.00 186.5513 22.13 45.81 3.75 3.75 18.75 0.25 0.13 100.00 194.5714 0.00 67.69 0.00 0.00 30.00 0.50 0.00 100.00 198.1915 0.00 59.50 0.00 0.00 0.00 0.00 0.00 100.00 159.5016 76.22 0.00 0.00 15.00 0.00 0.00 0.00 100.00 191.2217 82.06 0.00 15.00 0.00 15.00 0.50 0.00 100.00 212.5618 0.00 45.72 15.00 15.00 0.00 0.50 0.00 100.00 176.2219 76.31 0.00 15.00 0.00 0.00 0.50 0.00 100.00 191.8120 0.00 56.55 0.00 15.00 15.00 0.00 0.00 100.00 186.5521 0.00 45.28 30.00 0.00 0.00 0.00 0.00 100.00 175.2822 0.00 45.66 0.00 30.00 0.00 0.00 0.50 100.00 176.1623 66.00 0.00 30.00 0.00 0.00 0.50 0.50 100.00 197.0024 0.00 67.69 0.00 0.00 30.00 0.50 0.50 100.00 198.6925 92.00 0.00 0.00 0.00 15.00 0.00 0.50 100.00 207.5026 36.44 25.14 10.00 10.00 0.00 0.25 0.25 100.00 182.0727 86.62 0.00 0.00 0.00 0.00 0.50 0.00 100.00 187.1228 86.43 0.00 0.00 0.00 0.00 0.25 0.50 100.00 187.1829 0.00 59.75 0.00 0.00 0.00 0.50 0.50 100.00 160.7530 66.56 0.00 0.00 30.00 0.00 0.50 0.25 100.00 197.3131 81.69 0.00 15.00 0.00 15.00 0.00 0.50 100.00 212.1932 0.00 59.75 0.00 0.00 0.00 0.50 0.50 100.00 160.7533 48.88 33.72 0.00 0.00 30.00 0.00 0.00 100.00 212.5934 92.00 0.00 0.00 0.00 15.00 0.00 0.50 100.00 207.5035 0.00 45.28 30.00 0.00 0.00 0.00 0.50 100.00 175.7836 98.12 0.00 0.00 0.00 30.00 0.50 0.00 100.00 228.6237 0.00 45.66 0.00 30.00 0.00 0.00 0.00 100.00 175.6638 98.12 0.00 0.00 0.00 30.00 0.50 0.50 100.00 229.12

ANOVA TableLow-Energy Blunt Impact

Response: LE Blunt Transform: Natural log Constant: 1.99

Sum of Mean FSource Squares DF Square Value Prob > FModel 90.25 4 22.56 13.24 < 0.0001 significantA 25.75 1 25.75 15.11 0.0004B 5.05 1 5.05 2.96 0.0943D 1.25 1 1.25 0.74 0.3972BD 10.13 1 10.13 5.94 0.0201

Residual 57.93 34 1.70Lack of Fit 44.96 28 1.61 0.74 0.7297 not

significantPure Error 12.97 6 2.16Cor Total 148.18 38

The Model F-value of 13.24 implies the model is significant. There is only a 0.01% chance that a "Model F-Value" this large could occur due to noise.

Low-Energy Blunt Impact

DESIGN-EXPERT Plot

Ln(LE Blunt + 1.99)X = B: ATUY = D: GTS

Actual FactorsA: A2 = 0.38C: OP = 7.50E: GTMS = 0.25F: OS = 0.28

0.54

8.03

15.52

23.01

30.50

LE

Blun

t

0.0

7.5

15.0

22.5

30.0

0.0

7.5

15.0

22.5

30.0

B: ATU D: GTS

ANOVA TableHigh-Energy Blunt Impact

Response: HE Blunt Transform: Inverse sqrt Constant: 2.24

Sum of Mean FSource Squares DF Square Value Prob > FModel 1.56 8 0.19 4.52 0.0011 significantA 0.28 1 0.28 6.52 0.0160B 0.12 1 0.12 2.87 0.1007C 0.090 1 0.090 2.09 0.1588D 0.19 1 0.19 4.39 0.0448E 0.17 1 0.17 3.92 0.0570F 0.037 1 0.037 0.86 0.3606BD 0.30 1 0.30 6.87 0.0136CF 0.43 1 0.43 10.09 0.0034

Residual 1.29 30 0.043Lack of Fit 0.91 24 0.038 0.59 0.8333 not

significantPure Error 0.38 6 0.064Cor Total 2.85 38

The Model F-value of 4.52 implies the model is significant. There is only a 0.11% chance that a "Model F-Value" this large could occur due to noise.

DESIGN-EXPERT Plot

1.0/Sqrt(HE Blunt + 2.24)X = B: ATUY = D: GTS

Actual FactorsA: A2 = 0.38C: OP = 7.50E: GTMS = 0.25F: OS = 0.28

0

3

6

8

11

HE

Blun

t

0.00

7.50

15.00

22.50

30.00

0.00

7.50

15.00

22.50

30.00

B: ATU D: GTS

High-Energy Blunt Impact

Response: HE Sharp Transform: Square rootConstant: 7.84

Sum of Mean FSource Squares DF Square Value Prob > FModel 1342.46 8 167.81 24.41 < 0.0001

significantA 1004.82 1 1004.82 146.19 < 0.0001B 71.07 1 71.07 10.34 0.0031D 19.44 1 19.44 2.83 0.1030E 15.29 1 15.29 2.23 0.1462F 0.22 1 0.22 0.032 0.8590E2 50.30 1 50.30 7.32 0.0111AD 85.92 1 85.92 12.50 0.0013EF 174.46 1 174.46 25.38 < 0.0001

Residual 206.20 30 6.87Lack of Fit 171.12 24 7.13 1.22 0.4346 not

significantPure Error 35.08 6 5.85Cor Total 1548.66 38

The Model F-value of 24.41 implies the model is significant. There is only a 0.01% chance that a "Model F-Value" this large could occur due to noise.

ANOVA TableHigh-Energy Sharp Impact

Tail-Hook Impact ResistanceHigh-Energy Sharp

DESIGN-EXPERT Plot

X = Polyamine Curing Agent 2Y = Modifier 3

Actual FactorsB: Modifier 1 = 0.00C: Modifier 2 = 0.00E: A.P. 1 = 0.50F: A.P. 2 = 0.00

6

112

217

323

429

H

E S

har

p

0.00

0.25

0.50

0.75

1.00

0.00

7.50

15.00

22.50

30.00

Polyamine Curing Agent 2 Mod 3

DESIGN-EXPERT Plot

X = AP 1Y = AP 2

Actual FactorsCuring Agent 2 = 0.00Modifier 1 = 23.11Modifier 2 = 0.00Modifier 3 = 0.00

0

26

52

78

103

HE

Sha

rp

0.00

0.13

0.25

0.38

0.50

0.00

0.13

0.25

0.38

0.50

AP 1 AP 2

Tail-Hook Impact ResistanceHigh-Energy Sharp

ConstraintsLower Upper Lower Upper

Name Goal Limit Limit Weight Weight ImportanceA2 is in range 0 1 1 1 3ATU is in range 0 30 1 1 3OP is in range 0 30 1 1 3GTS is in range 0 30 1 1 3GTMS is in range 0 0.5 1 1 3OS is in range 0 0.5 1 1 3HE Sharp minimize 0 784 1 1 5

Solutions

ID A2 ATU OP* GTS GTMS OS HE SharpDesirability1 0.00 20.25 0.00 0.86 0.50 0.00 3 0.983

2 0.00 11.65 9.18 9.17 0.50 0.00 6 0.9633 0.00 23.17 3.98 2.65 0.00 0.50 9 0.9464 0.00 17.54 2.80 3.37 0.00 0.50 16 0.9185 0.00 17.26 2.74 0.00 0.00 0.50 20 0.9036 0.00 20.96 0.00 0.12 0.50 0.22 22 0.8967 0.02 13.35 0.00 16.65 0.00 0.36 29 0.8728 0.00 0.88 9.67 19.03 0.00 0.50 30 0.8699 0.00 2.65 0.00 7.15 0.50 0.15 36 0.84810 0.00 10.02 0.00 0.00 0.49 0.30 56 0.794

OptimizationHigh-Energy Sharp

Results

Based on the results of this study, two candidate formulations have been identified which provide improved performance in blunt and sharp impact resistance. These formulations are unique blends which did not appear in the original DOE.

Team Participants

Applied Research LaboratoryEpoxy Chemicals, Inc.Pratt & Whitney AutomationSt. Gobain Mineral Abrasives