DOE

Designed experiments play an important role in quality improvement. This section will introduce the basic concepts involved and it will contrast the statistically designed experiment with the one variable at a time approach that has been used traditionally. Also briefly discussed are the concepts involved in Taguchi methods, statistical methods named after their creator, Dr. Genichi Taguchi.

The traditional approach vs. statistically designed experiments

The traditional approach, which most of us learned in high school science class, is to hold all variables constant except one. When this approach is used we can be sure that the variation is due to a cause and effect relationship. However, this approach suffers from a number of problems:

• It usually isn t possible to hold all other variables constant.

• There is no way to account for the effect of joint variation of independent variables, such as interaction.

• There is no way to account for experimental error, including measurement variation.

The statistically designed experiment usually involves varying two or more variables simultaneously and obtaining multiple measurements under the same experimental conditions. The advantage of the statistical approach is three-fold:

1. Interactions can be detected and measured. Failure to detect interactions is a major flaw in the one variable at a time approach.

2. Each value does the work of several values. A properly designed experiment allows you to use the same observation to estimate several different effects. This translates directly to cost savings when using the statistical approach.

3. Experimental error is quantified and used to determine the confidence the experimenter has in his conclusions.