Viscosity evolution prediction (non linear platform)

[#1]

Hi all JMP user, 

I am trying to use several JMP tools to model and predict oil ageing as a function of temperature.

My model is calculated with the following equation:

η(t) model =η∞+(η0−η∞) e−kt with k=Aexp⁡(−EaRT)

In JMP, I defined η∞, A, and Ea as parameters (a, b, c), and I used the Nonlinear platform to estimate them by fitting the model to my viscosity measurements.

I have a few questions:

• I struggle to use the platform efficiently because I need to manually guess parameter values for a long time before the model converges to something reasonable.

• I noticed that the fitted parameters depend strongly on the initial values I provide. It seems that several different parameters can be found as long as you set up initially acceptable values. For me, that does not make sense. How should I handle this when I have no idea of the parameter values?

• I also tried using “Custom Inverse Prediction”, but I received an alert message. I guess that's means something is wrong with my model setup, so I should'nt trust my work :')

Any advice on how to properly set up and fit this type of Arrhenius‑based ageing model in JMP would be greatly appreciated. Thanks in advance