Feb 11 2022
Scientific Thinking and Manufacturing Improvement
“Scientific thinking” appears more and more in discussions of Lean, Kaizen, or TPS. What is it? Well, it’s the way scientists think. In reality, however, talk to actual scientists about PDCA, DMAIC, the 8D, A3 thinking, Why-Why analysis, TRIZ, or even statistical design of experiments, and their eyes glaze over. Most will have no idea what these methods are. This is true for physicists, chemists, biologists, or even economists. If you elaborate, they will dismiss these tools as trivial or devoid of any connection with their work.
Improving how things are made does make the world a better place but it’s not science. By growing a body of knowledge that is our greatest asset as a species, scientists make another contribution, that we should recognize as different.
Oct 12 2022
Musings on Large Numbers
Anyone who has taken an introductory course in probability, or even SPC, has heard of the law of large numbers. It’s a powerful result from probability theory, and, perhaps, the most widely used. Wikipedia starts the article on this topic with a statement that is free of any caveat or restrictions:
This is how the literature describes it and most professionals understand it. Buried in the fine print within the Wikipedia article, however, you find conditions for this law to apply. First, we discuss the differences between sample averages and expected values, both of which we often call “mean.” Then we consider applications of the law of large numbers in cases ranging from SPC to statistical physics. Finally, we zoom in on a simple case, the Cauchy distribution. It easily emerges from experimental data, and the Law of Large Numbers does not apply to it.
Continue reading…
Share this:
Like this:
By Michel Baudin • Laws of nature • 1