Nov 7 2022
Analyzing Variation with Histograms, KDE, and the Bootstrap
Assume you have a dataset that is a clean sample of a measured variable. It could be a critical dimension of a product, delivery lead times from a supplier, or environmental characteristics like temperature and humidity. How do you make it talk about the variable’s distribution? This post explores this challenge in the simple case of 1-dimensional data. I have used methods from histograms to KDE and the Bootstrap, varying in vintage from the 1890s to the 1980s:
Other methods were surely invented for the same purpose between 1895 and 1960 or since 1979, that I don’t know about or haven’t used. Readers are welcome to point them out.
The ones discussed here are not black boxes, automatically producing answers from a stream of data. All require a human to tune the settings of the tools. And this human needs to know the back story of the data.
Dec 1 2022
About Digital Twins
Some hosts showed digital twins during the Van of Nerds tour de France last September, but none mentioned the cyber-physical systems touted as a key component in Industry 4.0. Furthermore, we also found that the meaning of digital twin had drifted away from detailed simulations of physics and chemistry as part of a cyber-physical system for process control.
Instead, a digital twin is now an animation of part movements and machine status in a line for production control. This has effectively disabled discussions of digital twins in the context of cyber-physical systems, which matters in stabilizing and establishing capability for high-technology processes like additive manufacturing.
By Michel Baudin • Van of Nerds • 3 • Tags: cyber-physical system, digital twin, Process capability, process control, Production control