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Robust Design |
This example validates the robust design inner array with a two level factorial design and out array with a general full factorial design in DOE++.
Reference Case
The data is 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 actual factors is:
