Engineers and scientists often need to think in terms of mathematical functions or curves that describe behavior over time or under certain conditions, such as dose-response curves, chromatographic curves, viscosity versus shear, current versus voltage, and so on. In recent years, modeling data from design of experiments (DOE) has made it possible to just extract a number from the curve and apply classic DOE methods. With JMP Pro, you can directly model how the shape of the predicted curve changes as the input variables change. In JMP Pro, you can even define a "golden curve," the ideal curve you want to match. With just a few clicks, JMP Pro will find the combination of factor settings that best matches the golden curve. This technology has been widely used in areas such as bioassays, drug purity and stability studies, consumer products, and semiconductor research and development. We see a lot of interest in functional DOE analysis from many people in the industry. So in this talk, Chris will introduce the basic concepts of functional DOE analysis and use real case studies to show that anyone who uses JMP to analyze classical experimental data can easily get started with this technology.
