So I designed a RSM with JMP after having done the screening. I have 5 Input Variables and 5 output variables which are measured on the produced samples. So now I have those results of the responses and I have run the model using Model>Run Script. This of course takes me to the Least Squares fit and I went to the Prediction Profiler and Contour Profiler and there are already a suggested set of input parameters based on how I had designed the output responses i.e. whether it had to be maximised or minimised or matched to a target e.t.c. So my questions are in two parts;
1. I realised that on one of the responses (density) I had selected the maximise option instead of putting a target. The density of this material is about 1 g/cm3 and my results from experiments are in an acceptable range (0,7-09)range but the predicted output (because i had selected maximise) are being shown in the order of 1000s. And also the RSME is about 360! Is there a way for me to go back and adjust this in my RSM (and put limits) and evaluate the RSM again?
2. After one gets the desired settings by using the Prediction profiler, how is the model then generated or how does one come up with an equation to describe the model? Also when it comes to testing the model to show its suitablity, do I then have to use just this one suggested set of parameters and produce about 10 samples and evaluate if the result is as the predicted one for all of them?
I am hoping that someone here has had similar experiences and is able to help. I would also appreaciate being pointed to the right resources.
Thank you.
