Central Composite Response Surface Method: Difference between revisions

From ReliaWiki
Jump to navigation Jump to search
No edit summary
No edit summary
Line 1: Line 1:
{{Reference Example|{{Banner DOE Reference Examples}}}}
{{Reference Example|{{Banner DOE Reference Examples}}}}
This example validates the calculation of the central composite response surface method.
This example validates the calculation of the central composite response surface method in DOE++.


{{Reference_Example_Heading1}}
{{Reference_Example_Heading1}}
Line 80: Line 80:
|}
|}


The final equation in terms of actual values of these two factors is:  
The final equation in terms of the actual values of these two factors is:  


\[Yield= -1430.52285+7.80749×time+13.27053×temp-0.05505×〖time〗^2-0.04005×〖temp〗^2+0.01×time×temp\]
 
.




{{Reference_Example_Heading4|DOE++}}
{{Reference_Example_Heading4|DOE++}}

Revision as of 15:24, 25 June 2015

DOE Reference Examples Banner.png


New format available! This reference is now available in a new format that offers faster page load, improved display for calculations and images and more targeted search.

As of January 2024, this Reliawiki page will not continue to be updated. Please update all links and bookmarks to the latest references at DOE examples and DOE reference examples.




Central Composite Response Surface Method

This example validates the calculation of the central composite response surface method in DOE++.

Reference Case

Data is from Example 11-1 on page 431 in the book “Design and Analysis of Experiments” by Douglas C. Montgomery, John Wiley & Sons, 2001.

Data

Natural Variables Coded Variables Responses
A (time) B (temperature) A B Y( yield)
8076.580 170 -1 -1 76.5
80 180 -1 1 77
90 170 1 -1 78
90 180 1 1 79.5
85 175 0 0 79.9
85 175 0 0 80.3
85 175 0 0 80.0
85 175 0 0 79.7
85 175 0 0 79.8
92.07 175 1.414 0 78.4
77.93 175 -1.414 0 75.6
85 182.07 0 1.414 78.5
85 167.93 0 -1.414 77

Result

From the book, the ANOVA table is:

Source Sum of Squares ( Partial SS DF Mean Square F value Prob > F
Model 28.25 5 5.65 79.85 <0.0001
A 7.92 1 7.92 111.93 <0.0001
B 2.12 1 2.12 30.01 0.0009
A∙A 13.18 1 13.18 186.22 <0.0001
B∙B 6.97 1 6.97 98.56 <0.0001
A∙B 0.25 1 0.25 3.53 0.1022
Residual 0.5 7 0.071
Lack of Fit 0.28 3 0.094 1.78 0.2897
Pure Error 0.21 4 0.053
Total 28.74 12

The final equation in terms of the actual values of these two factors is:



Results in DOE++