R-DOE Design: Difference between revisions

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{{Reference Example|{{Banner DOE Reference Examples}}}}
{{Reference Example|{{Banner DOE Reference Examples}}}}
This example validates the calculation of the reliability DOE design.
This example validates the calculation of the reliability DOE design in Weibull++.


{{Reference_Example_Heading1}}
{{Reference_Example_Heading1}}
Data is from an example on page 530in the book ''Experiments, planning, analysis, and parameter design optimization'' by C.F. Jeff Wu, Michael Hamad, John Wiley & Sons, Inc. 2000.
The data are from an example on pages 530 and 544 in the book ''Experiments, Planning, Analysis, and Parameter Design Optimization'' by C.F. Jeff Wu, Michael Hamad, John Wiley & Sons, Inc. 2000.


{{Reference_Example_Heading2}}
{{Reference_Example_Heading2}}
Your text here.
 
{| {{Table}}
!rowspan="2" | Run
!colspan="5" | Factor
!rowspan="2" colspan ="2" | Failure Time
|-
!style="background:#f0f0f0;"|A
!style="background:#f0f0f0;"|B
!style="background:#f0f0f0;"|C
!style="background:#f0f0f0;"|D
!style="background:#f0f0f0;"|E
|-
| 1||-||-||-||-||-||(14, 16)||(20, <math>\infty\,\!</math>)
|-
| 2||-||-||+||+||+||(18,20)||(20, <math>\infty\,\!</math>)
|-
| 3||-||+||-||-||+||(8, 10)||(10, 12)
|-
| 4||-||+||+||+||-||(18, 20)||(20, <math>\infty\,\!</math>)
|-
| 5||+||-||-||+||-||(20, <math>\infty\,\!</math>)||(20, <math>\infty\,\!</math>)
|-
| 6||+||-||+||-||+||(12, 14)||(20, <math>\infty\,\!</math>)
|-
| 7||+||+||-||+||+||(16, 18)||(20, <math>\infty\,\!</math>)
|-
| 8||+||+||+||-||-||(12, 14)||(14, 16)
 
|}
 


{{Reference_Example_Heading3}}
{{Reference_Example_Heading3}}
Your text here.
 
From the book, the MLE and P values for the lognormal regression model are:
 
{| {{Table}}
 
!Effect
!MLE
!P value
|-
| Intercept ||2.939||0.00
|-
| A||0.117||0.06
|-
| B||-0.201||0.00
|-
| AB||-0.049||0.43
|-
| C||-0.051||0.41
|-
| D||0.273||0.00
|-
| E||-0.153||0.02
|-
|}
 


{{Reference_Example_Heading4|DOE++}}
{{Reference_Example_Heading4|DOE++}}
Your text here.
The software results match the book results. The MLE information table is:
 
[[Image:reliability_doe_mle_info.png|center]]

Latest revision as of 21:09, 18 September 2023

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R-DOE Design

This example validates the calculation of the reliability DOE design in Weibull++.

Reference Case

The data are from an example on pages 530 and 544 in the book Experiments, Planning, Analysis, and Parameter Design Optimization by C.F. Jeff Wu, Michael Hamad, John Wiley & Sons, Inc. 2000.

Data

Run Factor Failure Time
A B C D E
1 - - - - - (14, 16) (20, [math]\displaystyle{ \infty\,\! }[/math])
2 - - + + + (18,20) (20, [math]\displaystyle{ \infty\,\! }[/math])
3 - + - - + (8, 10) (10, 12)
4 - + + + - (18, 20) (20, [math]\displaystyle{ \infty\,\! }[/math])
5 + - - + - (20, [math]\displaystyle{ \infty\,\! }[/math]) (20, [math]\displaystyle{ \infty\,\! }[/math])
6 + - + - + (12, 14) (20, [math]\displaystyle{ \infty\,\! }[/math])
7 + + - + + (16, 18) (20, [math]\displaystyle{ \infty\,\! }[/math])
8 + + + - - (12, 14) (14, 16)


Result

From the book, the MLE and P values for the lognormal regression model are:

Effect MLE P value
Intercept 2.939 0.00
A 0.117 0.06
B -0.201 0.00
AB -0.049 0.43
C -0.051 0.41
D 0.273 0.00
E -0.153 0.02


Results in DOE++

The software results match the book results. The MLE information table is:

Reliability doe mle info.png
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