cancel
Showing results for 
Show  only  | Search instead for 
Did you mean: 
Try the Materials Informatics Toolkit, which is designed to easily handle SMILES data. This and other helpful add-ins are available in the JMP® Marketplace
Choose Language Hide Translation Bar

Mixture DOE

Hello,

Maybe an easy question!

I have 6 mixture components. I am interested in finding the effect of two of them on the response. There is also process variables, "time" and "temperature". Not sure how to set up this experiment.

4 REPLIES 4
GregF_JMP
Staff

Re: Mixture DOE

Hello MV1-

Trying to understand the scenario described as 6 Mixture Components, but only interested in two (let's call them A and B), versus four (C,D,E,F ) that are "not interesting".

Is the blend of C,D,E,F previously established and intended to not vary in relation to each other? 
    Can A and B both go to zero (leaving only CDEF)?
    As A and/or B increases in the mixture- does this displace CDEF?

 

On first glance maybe this is a 3 component mixture: A, B and "Fixed Blend CDEF"

 

 Please elaborate on what is assumed versus needs exploration for this designed experiment... 

Re: Mixture DOE

Thanks GregF_JMP,

actually all factors (A-F) are interesting, but one engineer experimented with factor A and B and temperature only. A-F are all ingredients going into product, say P. What he did was to use the factors A and B as present, absent. He then concluded presence of factor A is important. I do not trust the analysis and all other 4 ingredients, though present, but not par of the design. He simply used a factorial design. I know this sounds like a very convoluted DOE, but it lead me to think if there is any way to focus on two ingredients A and B when designing mixture DOE. Also, it may help to know each ingredient has a low/high limits in proportion. 

Hope this helps shed some light into this problem. The problems statement I realize may still be vague, for which I apologize. 

statman
Super User

Re: Mixture DOE

Sounds more to me you need to do some screening before you optimize with a mixture design.

 

John A. Cornell is recognized as one THE experts on mixture designs.  I recommend his papers "Embedding Mixture Designs inside Factorial Experiments", "Mixture Experiment Approaches: Examples, Discussion, and Recommendations".  Also Ron Snee has some good papers "Screening Concepts and Designs for Experiments with Mixtures" and "Design and Analysis of Mixture Experiments".  

"All models are wrong, some are useful" G.E.P. Box

Re: Mixture DOE

Thanks for your recommendation ... will be looking at this for sure.