May 19, 2020 7:59 AM
| Last Modified: May 21, 2020 9:29 AM
Curve, or "functional," data is everywhere. It occurs whenever we measure something over a continuum, like measuring temperature over time, pressure gradient across space, or radiation absorption across wavelength. In the image above, we have particle size measured over time while milling pigment for making LCD screens.
Sometimes, the shapes of the curves we measure are important to us, and we want to know how curve shape is affected by certain factors. For example, how is the pigment size-over-time curve affected by how we run our milling process? That's a complex question, in part because curve shape is a complex thing. How do we figure out how some factors might affect it?
The answer: functional design of experiments. Watch the video below to see how it's done in JMP.
This video assumes that you're already familiar with the basics of DOE in JMP. If you're not, check out this on-demand webinar or, if you already have JMP and prefer a hands-on introduction, JMP's DOE Intro Kit.