I am trying to use Custom Design to screen some material composition and process variable factors within my experimental system. My experimental setup is perhaps a little convoluted but I will explain the best I can.
My factors are as follows:
Material components:
- Monomer type: Categorical, 2 levels.
- Photoinitiator content: Continuous.
- Photoabsorber content: Continuous.
- Monomer Mixture (3:2): Continuous. (this is the content of a predetermined ratio of monomers at a 3:2 ratio)
- Multicrosslinker content: Continuous.
Process variables:
Questions:
- I used literature to inform the monomer mixture ratio contents. Could or should I be better off coding the Monomer Mixture (3:2) as two separate continuous factors at this screening stage instead of adding them as a single factor?
- According to the Mixture_with_Process JMP scripting guide, evaluation of the design should be done based off the prediction variance profile, design space plot and design diagnostics. I tried to evaluate this custom design in the same way (see Mixture-ProcessVarbables_Custom Design Evaluations.pdf) but have several confusions:
- the Prediction Variance > Max Desirability option is greyed out
- the design evaluation has not output all the stats for Design Diagnostics Outline
- The power analysis for my factors are on a whole pretty low. I have no idea if this is the best design to go with this type of screening experiment. If you can suggest alternative ways to design this, I would appreciate your input.
