Thanks @Victor_G,
You sound like you are familiar with pharmaceutical formulation work so I will give you bit more details.
Yes, it is a pure mixture problem where I have fixed total quantity and vary the amount of each factor.
So as you said, F1+F2+F3+F4 should be 100. I wanted to have 'at least' 3 levels for each factor and tried custom design but with that I could not achieve the orthogonality of main factors. I remember reading something like "make the model fit the problem does not make the problem fit the model." in one of postings in JMP community. However, I really wanted to employ DSD as it enables orthogonal evaluation of each factor on responses.
So, I made little trick to be able to apply DSD on this problem. I converted % of each factor to ratios and this way you can independently change the level of each factor. For instance, when you look at the screen shot of maximizing the desirability on my initial posting, JMP tells me that at F1:30, F2:5, F3:10, F4: 1 I can maximize the responses. This is the ratios, but I can convert this ratio to F1: 65%, F2: 11%, F3:22%, F4: 2%, then use this mixture to screen the formulations.
I know it is not strict forward and not sure if it is correct way to do it, but at least JMP fit this data nicely with p-value of predictive plot of R1&R2 ~0.01 and R3&R4 ~ 0.06.
I have never explored Mixture Design but will do if that enables the orthogonal design and less runs for initial screening compared to DSD.
Below I aggregated my response to your answer 1,2, and 3.
I have rated the importance of each response and applied "Maximize Desirability" to find desirability that is shown in my initial posting (2nd screenshot). As you have suggested, my goal is to definitely optimize the formulation by looking at the smaller design space. The question is what is smart ways to set up the boundary of design space to follow up. Assuming that subject matter expert wants me to fix F1 and F4 at the value suggested by desirability function of JMP (2nd screenshot) and further investigate the different ratio of F2 and F3. How should I set the boundary of F2 and F3 to look at? I see some people use 3D scatter plot to figure this out but since I would like to consider 4 responses (simultaneously) to optimize, it is not viable option. But I was thinking JMP should have some smart tool to help users to identify the design space to follow up even though there are multiple responses. In terms of designing method, I was not aware of Augment Design tool. Thanks for letting me know, I will look into it.
Thanks for your input and suggestions. I am very new to DOE and JMP so I am in the active learning phase. Any additional advice would be appreciated.