I'm no expert on the notion of 'proven acceptable range' but after some reading on the topic here's how I interpret the concept. You have a process with causal factors that influence variation in a response or responses. My understanding is (and I could be wrong or misled) the goal of 'proven acceptable range' investigations is to determine the range of values for the causal factors that yield a response within some limits. Call them 'spec limits', with a high degree of certainty.
Here's the rub. With OFAT experimentation you are probably not using experimental resources in as efficient manner as you could be, that is using design of experiments methods. OFAT really also limits you wrt to any modeling (main effects only...impossible to detect interactions...and lots of noise with no internal averaging of the factors inherent in DOE and problems on and on) that you'd need to do to quantify and characterize the relationship between the factors and responses. So at the end of the day...yes it's possible to use JMP, don't even really need JMP Pro, to conduct a 'proven acceptable range' investigation. You can collect the data, build a model, use Monte Carlo simulation wrt to the model, and come up with a 'proven acceptable range' but using OFAT as the means to get there...unless it's the only way, and I mean only way to get there...sorry...I'd never go down this path.
Especially in a pharma or life sciences based study. It's DOE or bust.
