AFAIK, in the custom design platform, as long as you select Necessary (vs. If Possible), JMP will create a design that will allow for estimation of those effects.
I do not mean to contradict one of my colleagues, but how does one specify the factors, model, and number of runs in order to get 'correct design' without correlated estimates?
I added four continuous factors representing concentration, temperature, time, and pressure. I added terms for the second and third power of each factor to the linear model. I used the default number of runs. This example is clearly not one of the correct results:
I simulated the response so that I could launch Fit Least Squares platform. The response is not involved in the correlation of the estimates, which is also indicated by VIF > 1 in the parameter estimates report. Here is the design:
Here is the report using the default coded levels. VIF around 10 indicates a correlation around 0.9.
Here is the same analysis but without coded levels. The coding clearly helps:
What is the use of the map of correlations if it does not represent the actual correlations? (I think that it does.)