What is DOE?

(Design of Experiments!)

Experimental Designs are used to identify or screen important factors affecting a process, and to develop empirical models of processes. Design of Experiment techniques enable teams to learn about process behaviour by running a series of experiments, where a maximum amount of information will be learned, in a minimum number of runs. Tradeoffs as to amount of information gained for number of runs, are known before running the experiments.

A typical plant Designed Experiment has 3 factors, each set at two levels - typically the maximum and minimum settings for each of the factors. A Designed Experiment with 3 factors each at 2 levels, is called a 2³ factorial experiment (or Taguchi L₈ experiment), and requires 8 runs, as follows:


run number	Factor A	Factor B	Factor C
1	lo	lo	lo
2	hi	lo	lo
3	lo	hi	lo
4	hi	hi	lo
5	lo	lo	hi
6	hi	lo	hi
7	lo	hi	hi
8	hi	hi	hi

Each row represents an experimental run - a set of conditions for the three factors. After the above 8 runs have been completed, and measured response recorded for each run, an empirical model may be built to predict process behaviour based on the settings of these factors. Fractional factorial experiments efficiently learn about several factors affecting a process - for instance a 2 ^8-4 fractional factorial experiment requires 16 runs, and allows up to 8 factors to be varied at the same time (in a particular or designed way).

And, after a Designed Experiment, the analysis is straightforward, you learn about interactions, and can predict future behaviour of the process!

If you're interested in Taguchi designs, you should look at the differences between Classical and Taguchi DOE, Classical and Taguchi designs, and Why Learn Classical DOE ?

Learn how to set up, run, analyse and present designed experiments, at our intensive hands on Design of Experiments Workshop.