Design of Experiments

The statistical analysis of the full factorial DOE results in the determination of the coefficients for a design space equation that relates all the control factors to the response factors. This equation includes interaction effects between control factors. This equation can then be used by designers to solve for the best overall system performance.

Minitab is the statistical analysis software application that is most often used with Lean Six Sigma projects. Minitab has a Wizard that guides you through the setup and design of a Design of Experiments study. This lesson demonstrates how to use that Wizard.

One of the most common techniques for analyzing the results of a DOE study in Minitab is to review the factor plots. These will provide insight into the optimal settings for control factors. The interactive plots will also highlight the settings associated with local maximum or minimum performance levels.

The DOE results can be used by design teams to make wise design decisions. This lesson will address how to use the DOE results in predicting system performance, designing system controls and establishing tolerances on system control and response factors.

Some DOE analyses will indicate that the optimal performance of the system would occur when control factors are set beyond the bounds of the study. When this occurs, it is best to shift the study to the likely region of optimal performance and then determine the best control factor settings. Following the path of steepest ascent or descent will ensure that the new analysis is conducted in a region with maximum or minimum performance.

This final lesson reviews the key principles that must be followed when conducting a DOE study. It highlights the benefit of each and the dangers if the principle is not properly applied.