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- Fitting of the parameters of non-linear regression

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Jun 9, 2016 1:09 AM
(1129 views)

I can fit the data with non-linear function, namely Mechanistic Growth curve from the JMP library. See the example of the fit in the next figure. The fit equation is BA = a(1 - b e^{-c *PA}).

BA represents a parameter within sheet metal forming domain. I also now that this fit depends on the three parameters: P_{1} - tooling dimension, P_{2} - tooling dimension, and P_{3} - plate thickness. Is it possible to couple the parameters of the fit curve (a, b, and c) and (P_{1}, P_{2}, and P_{3})? I want to have equation in a form of BA = a(P_{1}, P_{2}, P_{3})(1 - b(P_{1}, P_{2}, P_{3}) exp^{-c(P1, P2, P3)*PA}).

What I've done so far is, I obtained the a, b, and c for every possible combination of P_{1}, P_{2}, and P_{3}. P_{1}, P_{2}, and P_{3} are not nominal parameters, however I've done full factorial analysis for all available tooling dimensions and thicknesses.

I don't see where I should go further. Is there a way to obtain this kind of equation or during the non-linear fit or after obtainment of parameters?

Thanks in advance for your help.

2 REPLIES

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Jun 9, 2016 6:12 AM
(985 views)

Hi! Since you know the relationships you could do this by doing a custom model in the nonlinear platform. Setting up a custom equation is covered in Chapter 7 of the "Specialized Models" book found under Help > Books > Specialized Models.

Best,

M

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Mar 22, 2018 8:44 AM
(346 views)

Just a follow up to my previous comment.

Susan Walsh did a paper on this (link) that goes through the platform in deep detail.