Figure 2.2 Framework for Experimental Design
You perform the first three steps in the DOE platforms. The end result is a design that can be run in your work environment. For a detailed description of the workflow for these three steps, see The DOE Workflow: Describe, Specify, Design.
Your assumed model is an initial model that ideally contains all the effects that you want to estimate. In some platforms, you can explicitly build the model of interest. In others, the model is implicit in the choices that you make. For example, in the Screening Design platform, you might select a model with a given resolution. The resolution of the design determines which effects are confounded. Confounding of effects potentially leads to ambiguity about which effect is truly active.
The next step is the data collection phase, where the experiment is run under controlled conditions.
The example in The Coffee Strength Experiment explicitly illustrates the steps in the DOE workflow process. It also shows how to use a data table script to analyze your experimental data. Many examples in the Design of Experiments Guide illustrate both the workflow that supports a good design and the analysis of the experimental data from the study.