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In a Taguchi OA design in DOE++, how can I avoid aliasing the interactions I want to investigate?



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When working with a Taguchi orthogonal array, it can be hard to know how to assign factors to the appropriate columns of the array. For example, consider a simple L8(2^7) design, which uses 8 experimental runs to investigate up to 7 two-level factors. If you have only 3 factors, which 3 columns in the array should be used?

The Synthesis version of DOE++ now provides the Specify Interaction Terms window, which helps you assign factors to columns in the orthogonal array in a way that will not alias main effects or any of the selected interaction terms with any other terms. In other words, it helps you configure a design that you can use to determine whether any of the main effects or selected interaction effects are significant.

While you're configuring a Taguchi OA factorial design, click the Additional Settings heading in the navigation panel and then click the Specify Interaction Terms link in the input panel.

Taguchi OA factorial design

Using this tool always avoids aliasing main effects, so you just need to specify the interaction effects that you want to investigate. To add an interaction effect, click the first row in the table and specify the interaction using the drop-down lists in that row. For example, if you wish to include the interaction term AC, select factor A in the first drop-down list and factor C in the second. Once you click outside the row, the interaction term (e.g., "A·C") will appear. (If you want to remove the term, click inside its row and then click the red X.).

Selected interactions

After you click OK, the software will attempt to assign factors to the appropriate columns in the orthogonal array. In the example shown next, when AC is specified as an interaction term, Factor 1 is now assigned to column 1, Factor 2 to column 4, and Factor 3 to column 2.

Assigned columns

To ensure that you will be able to investigate the main effects and the interactions you entered, do not change the new factor assignments.