Tag Archives: DOE

Taguchi Methods for Robust Design and the P-Diagram

In previous articles in this series I introduced Designed Experiments (Article 28) and Taguchi Methods (Article 32).   In this article I will introduce the Parameter Diagram, aka P-diagram, and explain how the P-diagram is used in conjunction with Designed Experiments as part of the robust design process. The P-diagram is used to classify all of […]

A Real World Application of Design of Experiments

Black Belt students are exposed to Design of Experiments (DOE) in their classroom training, but in my experience very few of them actually apply the technique while completing a project to earn their Black Belt certificate.  One of my students recently completed a project that made excellent use of a Designed Experiment, and his company […]

Shainin Methods

Previously we discussed Taguchi Methods as an alternative to classical Designed Experiments. Another approach to experimentation is Shainin Methods, as developed by Mr. Dorian Shainin and strongly advocated by Mr. Keki Bhote. The late Dorian Shainin began introducing a series of experimentation techniques in the 1930’s and continued his work for nearly 50 years. Keki […]

Taguchi Designed Experiments

Classical Designed Experiments (DOE) were discussed in a previous article in this series.  In the last article we discussed descriptive statistics that describe the center of an output or response (mean, median and mode) and the amount of variability in the output or response (range, standard deviation and variance). Taguchi Designed Experiments are an alternative […]

Designed Experiments – A High Level Introduction

In an earlier article, I discussed the transformation function Y = f(X), where Y represents the output of a process.  The output is a function of the inputs (the X’s) that affect the output. Designed Experiments are used to help us quantify the effect that the inputs have on the output of a process.  In […]