The following example, adapted from Meyer, et al. (1996), shows how to use the Screening Design platform when you have many factors. In this example, a chemical engineer investigates the effects of five factors on the percent reaction of a chemical process. The factors are:
The Temperature*Concentration interaction is active, so you want a design that does not alias this interaction with a main effect.
The Catalyst*Temperature* interaction is not likely to be active.
The Stir Rate*Concentration interaction is not likely to be active.
1.
Select DOE > Classical > Screening Design.
2.
Double-click Y under Response Name and type Percent Reacted.
Note that the default Goal is Maximize. The Goal is to maximize the response, but the minimum acceptable reaction percentage is 90 (Lower Limit) and the upper limit is 100 (Upper Limit).
See Figure 8.19 for the completed Responses outline. Now, specify the factors.
To enter the factors automatically, use the Reactor Factors.jmp data table:
1.
Select Help > Sample Data Library and open Design Experiment/Reactor Factors.jmp.
1.
Add five continuous factors by entering 5 in the Add N Factors box and clicking Continuous.
2.
Change the default factor names (X1-X5) to Feed Rate, Catalyst, Stir Rate, Temperature, and Concentration.
Figure 8.19 Responses and Factors Outlines
1.
Click Continue.
2.
From the Choose Screening Type panel, accept the default selection to Choose from a list of fractional factorial designs and click Continue.
Figure 8.20 Fractional Factorial Designs for Five Continuous Factors
In this example, you want to know whether the Temperature*Concentration interaction is confounded with a main effect. Use the Display and Modify Design outline to view the aliasing structure for the design that you selected and to change it, if appropriate.
Figure 8.21 Aliasing of Effects Outline
The Temperature*Concentration interaction, which you suspect is active, is confounded with Feed Rate, a main effect. You want to change the generating rules to construct a design where Feed Rate is aliased with effects that you suspect are inactive, and where the Temperature*Concentration interaction is not aliased with a main effect.
The default-generating rules give you the standard (or principal) one-quarter fraction of the full factorial design. Recall that you suspect that the Catalyst*Temperature and Stir Rate*Concentration interactions are not likely to be active. Redefine the generating rules so that these two interactions are confounded with Feed Rate. The redefined generating rules give you a different one-quarter fraction of the full factorial design.
Deselect Stir Rate in the Temperature column.
Deselect Catalyst in the Concentration column.
Select Feed Rate in the Concentration column.
Figure 8.22 New Generating Rules
4.
Click Apply.
Figure 8.23 Aliasing of Effects Outline for Modified Generating Rules
In the design that you have defined, Feed Rate is confounded with Catalyst*Temperature and Stir Rate*Concentration. Also, the Temperature*Concentration interaction is now confounded with the two-way interaction Catalyst*Stir Rate.
Figure 8.24 Eight-Run Fractional Factorial Design Table
The Screening, Model, and DOE Dialog scripts are also included. For details about these scripts, see Make Table.
1.
Select Help > Sample Data Library and open Design Experiment/Reactor 8 Runs.jmp.
2.
Run the Screening script in the data table.
The Screening script launches the Screening platform (Analyze > Specialized Modeling > Specialized DOE Models > Fit Two Level Screening) for your response and factors.
Figure 8.25 shows the report.
Figure 8.25 Report for Screening Example
Note: Since the p-values are obtained using a simulation-based technique, your p-values might not precisely match those shown here.
The report shows both Individual and Simultaneous p-values based on Lenth t-ratios. None of the effects are significant, even with respect to the Individual p-values. The Half Normal Plot suggests that the effects reflect only random noise.

Help created on 7/12/2018