For the latest version of JMP Help, visit JMP.com/help.


Publication date: 11/29/2021

Constraints

Once you complete the Factors outline, click Continue. The Define Factor Constraints outline appears. Use this outline to restrict the design region. For more information about the outline, see Define Factor Constraints.

You can use the Use Disallowed Combinations Filter and Use Disallowed Combinations Script options to specify disallowed factor level combinations. Or, you can use the Specify Linear Constraints option to specify bounds in terms of linear inequalities. However, the design is generated differently for these two methods.

Use Disallowed Combinations Filter and Use Disallowed Combinations Script

When disallowed combinations are specified, the random points that form the basis for the clustering algorithm are randomly distributed within the unconstrained design region. Then disallowed points are removed and clustering proceeds with the remaining points.

Note: Depending on the nature of the constraints and the specified Number of Runs, the default coverage of the unconstrained design space by the initial randomly generated points might not be sufficient to produce the required Number of Runs. In this case, you might obtain a JMP Alert indicating that the algorithm “Could not find sufficient number of points.” To increase the initial number of points that form the basis for the clustering algorithm, specify a larger average number of initial points per design point by selecting Advanced Options > Set Average Cluster Size. (See Set Average Cluster Size for FFF Designs).

Specify Linear Constraints

When you use the Specify Linear Constraints option, the random points that form the basis for the clustering algorithm are randomly distributed within the constrained design region. The clustering algorithm uses these points.

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