Response_surface_methodology
DEVELVE
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Easy to use Statistical software
Response Surface Methodology (RSM)
Response Surface Methodology is a statistical test setup with more factors on different levels combined in one experiment. It is used when analyzing complex problems with a multiple of influence factors in once including interactions. This is done by using test arrays. A RSM is
This document is an introduction of the RSM functionality of Develve for more information how to conduct a RSM see
Select DOE in the statistical mode drop-down menu to start a Design of experiment. The data of the input table is sorted according the factorial table (see example). With this option it is possible to conduct a RSM with various arrays.
For calculating the statistical properties of a data set the data must entered in the input table 1. The data will sorted according the Factorial table 9. and the result will be displayed in the result array 3. and Graph image 2.
9) Factorial table
In this table the coded array is visible. This must be coded and may not be renamed like in a always works with coded arrays!
Example
First select a array (DOE => Factorial Array).
Mostly used for the RSM are Box-Behnken and Central Composite (CCD) arrays.
Compared
Box-Behnken design Central Composite design
Extreme combinations No Yes
Size of matrix Smaller Bigger
Amount of levels 3 5
No Circumscribed points The Circumscribed point especially
for the bigger arrays are far from
the normal setting
Select array
Add data
The test array will be added in the Factorial table.
Now the test results put in the input table
See
Select the Response surface box (DOE => Response surface) for the statistical analysis.
In this window you can select the factors to include in the Response surface. Develve will calculate the coefficient of the selected factors and if it is significant. See
Colors of the cells
-
Green
Not significant
-
Yellow
Significant
Response Surface Graph
Display the Response Surface Graph by clicking on Graph.
By clicking on the graph the calculated result will pop-up with coded input value.
single response 2D graph 3D response graph
By right click on the graph one of the responses can be displayed in 2 or 3D.
Extrapolation of the result
Without extrapolation With a extrapolation of 2
Be careful with extrapolation of data!
Links
Response Surface Methodology is a statistical test setup with more factors on different levels combined in one experiment. It is used when analyzing complex problems with a multiple of influence factors in once including interactions. This is done by using test arrays. A RSM iswith specially designed arrays for calculating interactions and quadratic responses.This document is an introduction of the RSM functionality of Develve for more information how to conduct a RSM seeSelectin the statistical mode drop-down menu to start a Design of experiment. The data of the input table is sorted according the factorial table (see example). With this option it is possible to conduct a RSM with various arrays.For calculating the statistical properties of a data set the data must entered in the input tableThe data will sorted according the Factorial tableand the result will be displayed in the result arrayand Graph image9) Factorial tableIn this table the coded array is visible. This must be coded and maybe renamed like in a, a RSMworks with coded arrays!First select a array (DOE => Factorial Array).Mostly used for the RSM are Box-Behnken and Central Composite (CCD) arrays.The test array will be added in the Factorial table.Now the test results put in the input tableSeeSelect the Response surface box (DOE => Response surface) for the statistical analysis.In this window you can select the factors to include in the Response surface. Develve will calculate the coefficient of the selected factors and if it is significant. Seefor the formula of the calculation.Display the Response Surface Graph by clicking on Graph.By clicking on the graph the calculated result will pop-up with coded input value.By right click on the graph one of the responses can be displayed in 2 or 3D.Be careful with extrapolation of data!