Publication date: 08/13/2020

Create the Design

Create the Strength 3 covering array by following these steps.

1. Select Help > Sample Data Library and open Design Experiment/Software Factors.jmp.

The Software Factors.jmp data table contains the factors and their settings.

2. Select DOE > Special Purpose > Covering Array.

3. From the menu next to Strength: t = , select 3.

4. Click the Covering Array red triangle, select Load Factors and click Continue.

The Factors outline is populated with the four factors and their levels.

Figure 20.4 Factors Outline for Software Factors 

5. Click Continue.

The Restrict Factor Level Combinations outline opens, where you can enter restrictions on the design settings. Because there are no restrictions for this design, do not change the default selection of None.

6. Click Make Design.

The Design outline opens to show a 45-run design.

Figure 20.5 Design and Metrics Outlines for Software Factors 

In the Metrics outline, consider the row that corresponds to t = 3. The Coverage is 100%, indicating that the design covers 100% of the three-factor interactions. This is what you want, because you requested a Strength 3 design. For t = 3, the Diversity column indicates that 68.33% of the three-factor interactions that appear are distinct. There is some minor repetition of three-factor combinations.

For t = 4, the Coverage is 50%, indicating that the design covers half of the four-factor interactions. There are 90 possible distinct combinations of the four factor settings. The 45 runs in the design comprise one-half of these distinct combinations. The Diversity value of 100% reinforces the fact that none of the four-way interactions are repeated.

7. Click Make Table.

Figure 20.6 Partial Design Table for Software Factors 

The design is presented in a data table. Notice the following in the Table panel at the top left:

The Design note indicates that this is a strength 3 covering array.

The DOE Dialog script reproduces the Covering Array window settings.

The Analysis script analyzes the experimental data.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).
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