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Functional Data Explorer - How can I match two (or more) functional responses simultaneously

I see how to use the FDE when I have a DOE with a functional response and want to determine how to set my DOE x's to minimize the difference in the response function to a target function (desirability function tools used).

 

How can this be extended so that two separate response functions can be modeled and used to select the optimum DOE settings to minimize the difference in both functional responses relative to each of their targets? 

 

I would prefer an interactive explanation.

 

Example from JMP sample data  

kpgallagher_ppg_3-1588280568435.png

 

 

kpgallagher_ppg_0-1588279258486.png

kpgallagher_ppg_1-1588280194986.png

kpgallagher_ppg_2-1588280238200.png

 

 

Kevin Gallagher
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Re: Functional Data Explorer - How can I match two (or more) functional responses simultaneously

Can you create a difference column with a desirability function for minimize? That is, save the FPCs and the supplementary variables for each functional response, use a column formula to compute the difference in FPCs, and then use Graph > Profiler with the option to use original factors?

Learn it once, use it forever!

View solution in original post

3 REPLIES 3
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Re: Functional Data Explorer - How can I match two (or more) functional responses simultaneously

Can you create a difference column with a desirability function for minimize? That is, save the FPCs and the supplementary variables for each functional response, use a column formula to compute the difference in FPCs, and then use Graph > Profiler with the option to use original factors?

Learn it once, use it forever!

View solution in original post

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statman
Level VII

Re: Functional Data Explorer - How can I match two (or more) functional responses simultaneously

Is there any relationship between the two functional responses?  Have you done Multivariate>Multivariate analysis of the multiple response functions?

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Re: Functional Data Explorer - How can I match two (or more) functional responses simultaneously

Yes, this is always a good approach. In the Mill Data example, there is a relationship. I was thinking of a case where there is not a strong relationship between the two functions but getting a formulation that matches both functions would be desirable.
Kevin Gallagher
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