In industrial R&D and process improvement we experiment to understand complex, multifactor systems. There has been tremendous interest in applying "Bayesian optimization" or "Active Learning" to efficiently innovate new products and processes. These approaches to sequential experimentation promise greater speed while…
In industrial R&D and process improvement we experiment to understand wickedly complex, multifactor systems. Empirical models of our processes enable us to bring new technologies to market and deliver consistent quality for our customers. Statistical Design and Analysis of Experiments (DOE) is a proven methodology for…
I sometimes get questions about how to select the "best" model from experiments with blocks. We recommend that you model blocks as random effects, which means that you can't use Stepwise or Generalized Regression personalities for model selection because they only support fixed effects. In this video I talk about: * Why we…
Scientists and engineers from a variety of different industries came to Wolfson College, University of Cambridge to learn about a smarter way to do experiments. Presenters from JMP (including me, @Phil_Kay ) and Prism Training and Consultancy showed how to learn about processes and systems in the most efficient way using…
"Have you run DOEs or built models in JMP? You all have? Then you are ready for this..."Selected JMP users joined Chris Gotwalt, JMP Chief Data Scientist, for a special hands-on workshop on Functional Data Explorer in JMP Pro. Chris has kindly agreed to making all the materials available for anyone to use. You can find…
Design of Experiments (DoE) is one of the most important data science tools for scientists and engineers. I set out to write a series of blog posts to demystify DoE with simple explanations of some of the terms and concepts that can be confusing for people when they are starting out. Click here for links to all 7 posts in…
I created a tutorial workshop with a case study on a fermentation process for a Design of Experiments course for bioscientists. Here you have the JMP journal and a pdf document with instructions. This tutorial will show you the overwhelming number of possibilities with multi-factor systems. And how you can efficiently and…
Here is part 1 of this 3-part series: And here is part 2: Finally, here is part 3: You can learn more from the DOE module of the free online Statistical Thinking for Industrial Problem Solving course. Enroll here. In this series I talk about: * Why you should use Design of Experiments, why you need to experiment to…
Attached are slides and exercises from the Functional Data Analysis Workshop. Chris Gotwalt, Director of Statistics R&D at JMP, presented on an introduction to Functional Data Analysis and using JMP Pro's Functional Data Explorer. Customers from Consumer Packaged Goods, Chemical, Semiconductor, Pharma/BioPharma and other…
A company was casting thousands of complex components every year and the defect rate was more than 10%. The cost of this high scrap rate was unsustainable: millions of dollars per year. Also, there was a big cost of lost sales and credibility because of more demand from customers than they could supply. Bringing in "big…
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