I want a space filling design with some continuous and discrete of categorical factors. Is it wise to quantize continuous factors or create logic in my experiment based on the values of continuous factors to achieve this effect?
Binning a continuous is certainly one way to do this. If you don't have too many categorical factors/levels, JMP 12 now allows categorical factors in Space Filling for Fast Flexible Filling Designs (Fast Flexible Filling Designs), so you may want to try that out.
These FFF fast flexible filling designs have a problem that I imagine stems from the clustering technique used to generate them. My experience so far is that they don't go all the way to the edge of the factor space. The picture I have in my mind is that the clusters would be bounded by the factor space and the final design point from the cluster would be in the interior of the cluster. This would lead to a buffering along the boundaries of the factor space and leave out the extreme points. Am I doing something wrong?
I've had another problem too. I added a "Disallowed Combination" that completely drives the algorithm crazy. It generates all manner of combinations outside the bounds defined when I added my continuous factors. I haven't even gotten to the point where I am binning the continuous values. I'm running version 11.1.
One of the new features in JMP 12 was to add the criterion of MaxPro (which is also the default) that does a better job at exploring the boundaries.
There was a bug in JMP 11.1 for non-convex regions with disallowed combinations if the centroid fell outside of the design range, that was fixed in JMP 11.2, so it's quite possible that you've run into that case.