Hi,
I conduct an optimization study using JMP Pro 17. My problem has 13 design variables and I try to perform a Screening Design.
I perform Screening Design from the ‘DOE --> Classical --> Two Level Screening --> Screening Design’ menu. As the Screening type I choose ‘choose from a list of fractional factorial designs’ (Picture1_DOE_ScreeningDesign).
The options I chose next are as follows:
‘Number of Runs: 32,
Block Size: -,
Deisgn Type: Fractional Factorial,
Resolution-what is estimable: 4- Some 2-factor interactions,
Run Order: Keep the Same,
Number of Center Points: 1’.
When I click on ‘Make Table’, the window ‘Fractional Factorial’ pops up (left part of Picture2_FractionalFactorial_FitModel).
After conducting the 33 experiments listed, I fill the Y column and I fit a model to the problem from the ‘Analyze --> Fit Model’ menu to conduct the Screening Design. On the ‘Fit Model’ window, JMP lists the default parameters on the ‘Construct Model Effects’, which includes main effects and some of the binary interactions (right part of Picture2_FractionalFactorial_FitModel). Additional parameters can also be added to this list by using Add and Cross buttons. When I try to add all of the binary and quadratic terms (Picture3_AllEffects_ParameterList), and hit the Run button, I see that some terms cause singularity, given in the Singularity Details list (Figure: Picture4_AllEffects_SingularityList or Picture5_X1X12_X2X5).
However, no singularity is obtained when only of the terms in each line of Singularity List is added to the ‘Construct Model Effects’ list, and each term on a single line results with the same Logworth value. What I guess is that, JMP builds the experiment set in ‘Fractional Factorial’ such that the effects of the terms given in one line of the singularity list are already taken into account. For example, 33 experiments are listed such that the effect (Logworth value) of ‘X1*X1 and X2*X2’ or ‘X1*X12 and X5*X2’ will always be the same. (Figure: Picture5_X1X1 and Figure: Picture6_X2X2 or Figure: Picture7_X1X12 and Figure8: Picture_X2X5)
If that is the case, I need a physical explanation on why I can not take the individual effects of all binary and quadratic effects into account. Is it possible to conduct a 2 level (by taking only the minimum and maximum values for each design variable) Screening Design study and taking all of the binary and quadratic interactions into account using JMP? Maybe choosing different options from the menu would help me.
Thank you for the answers in advance.
Best regards,
Ceyda Kavak
PS: I recently came across a similar discussion (Solved: No quadratic effects in Response surface experiment - JMP User Community), hence I would like to tag @statman . Thank you for your time and consideration.