157Mixture Designs to Optimize Pollution Level and Temperature of Fuels

the dialog box shown in Figure9.43 opens. Select “Target” for “Goal”, enter

“399” for “Lower”, and enter “400” for “Target” and “401” for “Upper”. (The

laboratory aims for a target temperature of 400 units.) Click on “OK” and the

optimal solution (X: 20%, Y: 35.6443%, and Z: 44.3557%) shown in Figure9.44

is the result.

FIGURE 9.38

Quadratic terms for fuel Zeo mixture design.

Analysis of Variance for Temperature (component proportions)

Source DF Seq SS Adj SS Adj MS F P

Regression 5 14933.7 14933.71 2986.74 416.36 0.000

Linear 2 5686.8 109.00 54.50 7.60 0.043

Quadratic 3 9246.9 9246.93 3082.31 429.69 0.000

X*Y 1 5775.6 5851.62 5851.62 815.74 0.000

X*Z 1 2346.0 2365.84 2365.84 329.81 0.000

Y*Z 1 1125.3 1125.35 1125.35 156.88 0.000

Residual Error 4 28.7 28.69 7.17

Total 9 14962.4

FIGURE 9.39

ANOVA output for fuel Zeo.

158 Six Sigma Case Studies with Minitab

®

FIGURE 9.40

Selection of “Response Optimizer” for fuel Zeo.

FIGURE 9.41

Available response variable for optimization for fuel Zeo.

159Mixture Designs to Optimize Pollution Level and Temperature of Fuels

FIGURE 9.42

Selection of response variable for optimization for fuel Zeo.

Temperature

FIGURE 9.43

Entry of bounds for temperature.

160 Six Sigma Case Studies with Minitab

®

9.4 Design and Verify Phases

Based on the results of the analyze phase, fuel Neo is designed to contain

only R (100%), and fuel Zeo is designed to contain 20% of X, 35.6443% of Y,

and 44.3557% of Z.

The laboratory runs additional experiments with the optimal proportions

of the respective components to test and verify the sulfation level for Neo

and the temperature for Zeo.

High

Cur

Low

D

1.0000

Optimal

Temperature

Target: 400.0

y = 400.0

d = 1.0000

Composite

Desirability

1.0000

[ ]:Y

60.0

[35.6443]

20.0

[ ]:Z

60.0

[44.3557]

20.0

[ ]:X

60.0

[20.0]

20.0

FIGURE 9.44

Optimal amounts of fuel Zeo components.

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