Here are my thoughts/questions/comments:
There are many questions before providing an appropriate response. I apologize, I think it is appropriate to consider why you want the experiment you are planning rather than just say here is how you create it in JMP. Feel free to ignore my thoughts if they are not useful.
It sounds like you have decided on 27 runs (treatment combinations)? Is this a Taguchi L27 design you want? Why? You want to do a fractional factorial, but you are testing factors at 3 levels? Why? Are you trying to do a screening design? You will be confounding 2nd order linear effects with non-linear effects. This doesn't really follow hierarchy guidelines. So this begs the question, what model are you trying to evaluate? Do you want to understand causal structure or "pick a winner"? Why 4 replicates? Estimating quadratic and cubic effects of a replicate is non-sensical. Can you get a reasonable estimate of noise using 2 replicates? You want 5 repeats of each treatment, why? Do you understand how you will use the repeats?
My advice is to think sequential experimentation. First evaluate the relative importance of the 11 factors by exaggerating each of their effects equally. Accomplish this by using 2-levels that are set boldly. This creates a design space. Determine if this space is appropriate. If not, move the space (by changing factors or factor levels), if it is, augment the space (add levels, center points, etc.). replication and repetition are 2 excellent strategies to handle noise. Repeats for short-term noise components (measurement, within sample, sample-to-sample) and replicates for long term noise components (raw materials, ambient conditions, etc.). You might consider blocking as strategy for replication. I would start with 2 extreme blocks. Much depends on the noise you are trying to "evaluate" or whether you are trying to be robust to noise.
"All models are wrong, some are useful" G.E.P. Box