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This example validates the robust design inner array with a two level factorial design and an out array with a general full factorial design in Weibull++.
Reference Case
The data are from the example on page 1252 in the book Applied linear Statistical Models by Michael H.K, Christopher J.N, John N. William. Li, Fifth Edition, McGraw-Hill, 2005.
Data
| Run
|
A
|
B
|
C
|
Noise Factor
|
| 60°F
|
70°F
|
80°F
|
90°F
|
| 1 |
1 |
1 |
1 |
48 |
49 |
56 |
63
|
| 2 |
1 |
-1 |
-1 |
50 |
52 |
55 |
63
|
| 3 |
-1 |
1 |
1 |
70 |
72 |
77 |
84
|
| 4 |
-1 |
-1 |
-1 |
42 |
65 |
70 |
73
|
| 5 |
-1 |
1 |
-1 |
61 |
70 |
78 |
79
|
| 6 |
-1 |
-1 |
1 |
65 |
74 |
74 |
77
|
| 7 |
1 |
-1 |
1 |
40 |
59 |
63 |
66
|
| 8 |
1 |
1 |
-1 |
48 |
51 |
55 |
60
|
.
Result
From the book the results are:
| Predictor
|
Coef
|
| Constant |
62.781
|
| A |
-7.906
|
| B |
1.031
|
| C |
2.031
|
| AB |
-2.156
|
| AC |
-1.406
|
| BC |
-0.969
|
| ABC |
0.594
|
Results in DOE++
The software results match the book results. The ANOVA table is:
The final equation in terms of the actual factors is:
