Setting up an screening design

[#1]

Hi,

we are currently trying to set up our first custom design but are struggling with the choices. Our problem is that we have 4 groups of factors: 1st group has 2 options, 2nd group 3 factors, 3rd group 4 factors and the 4th group only one factor - so in total 10 factors but they are continuous values. This is where we struggle to set it up. If they would be only categorical then we would just add categorical factors with certain amount of levels. 

What we already know from previous experiments: 

1. The concentration of each factor has a quadratic effect on the outcome. Meaning we do not only need to check the interactions but also check the interactions at different concentrations.
2. Only different factors of the 3rd group should be present at the same time in a run. Thus, we would need to set up constraints to not allow combinations of the 2 factors of the 1st group or the 3 factors of the 2nd group.

I tried a custom design where I added the 10 factors as continuous factors. Then I set up under "Define Factor Constraints" and "Use Disallowed Combinations Filter": factor 1 AND factor 2 (of group 1) OR factor 1 AND factor 2 AND factor 3 (of group 2). I made sure that the min and max values are included but what I cannot understand is that when adding the 2nd interactions the interaction factor 1*factor 2 is included as well as other combinations. So I think there is already an error. 

I did not know how to get rid of these unwanted interactions so I took the time to remove them manually from the list of 2nd and 3rd interactions but anyway these combinations are included after I continue to the table. 

How do I proceed with the design?

Thanks.

[#2]

It is conventional to linearly transform the factor levels (X) for several important benefits. The coding is simply (X-M)/H, where M is the mid-point between low and high setting ((high + low) / 2) and H is the half range ((high - low) / 2). So X1, X2, and X3 are now modeled on a scale-invariant basis. In your case, each factor in group 1 is using this approach by using a second factor, group 1 level, with the default coded levels -1 and +1.