In this example, you first perform a capability analysis for the three nonnormal variables in Tablet Measurements.jmp. You then use Simulate to find confidence limits for the nonconformance percentage for the variable Purity.
1.
Select Help > Sample Data Library and open Tablet Measurements.jmp.
2.
Select Analyze > Quality and Process > Process Capability.
3.
Select Weight, Thickness, and Purity and click Y, Process.
4.
Select Weight, Thickness, and Purity in the Cast Selected Columns into Roles list on the right.
5.
Open the Distribution Options outline.
6.
From the Distribution list, select Best Fit.
7.
Click Set Process Distribution.
The &Dist(Best Fit) suffix is added to each column name in the list on the right.
8.
A Capability Index Plot appears, showing the Ppk values. Note that only the Thickness variable appears above the line that denotes Ppk = 1. Purity is nearly on the line. Although the number of measurements, 250, seems large, the estimated Ppk value is still quite variable. For this reason, you construct a confidence interval for the true Purity Ppk value.
9.
Select Individual Detail Reports from the Process Capability red triangle menu.
Weight: Lognormal
Thickness: Johnson Sb (see the note immediately beneath the Thickness(Johnson) Capability report title)
Purity: Weibull
Weibull Parameter Estimates for Purity
1.
In the Tablet Measurements.jmp sample data table, select Cols > New Columns.
2.
Next to Column Name, enter Simulated Purity.
3.
From the Column Properties list, select Formula.
4.
In the formula editor, select Random > Random Weibull.
5.
The placeholder for beta is selected. Click the insertion element (^).
 
7.
Copy the entry in Row 2 in the Estimate column (1589.7167836).
8.
In the formula editor window, select the placeholder for beta in the Random Weibull formula and paste 1589.7167836 into the placeholder for beta.
10.
In the formula editor window, select the placeholder for alpha in the Random Weibull formula and paste 99.918708989 into the placeholder for alpha.
Completed Formula Window
11.
Click OK in the formula editor window.
The Simulated Purity column contains a formula that simulates values from the best-fitting distribution.
1.
In the Process Capability report, select Relaunch Dialog from the Process Capability red triangle menu.
3.
In the launch window, from the Cast Selected Columns into Roles list, select Weight&Dist(Lognormal) and Thickness&Dist(Johnson).
4.
Click Remove.
5.
6.
Select Individual Detail Reports from the Process Capability red triangle menu,
7.
In the Column to Switch Out list, Purity is selected. In the Column to Switch In list, Simulated Purity is selected.
8.
Next to Number of Samples, enter 500.
9.
(Optional) Next to Random Seed, enter 12345.
10.
The calculation might take several seconds. A data table entitled Process Capability Simulate Results (Estimate) appears. The Ppk and Ppl columns in this table each contain 500 values calculated based on the Simulated Purity formula. The first row, which is excluded, contains the values for Purity obtained in your original analysis. Because Purity has only a lower specification limit, the Ppk values are identical to the Ppl values.
Distribution of Simulated Ppk Values for Purity
Two Distribution reports are shown, one for Ppk and one for Ppl. But Purity has only a lower specification limit, so that the Ppk and Ppl values are identical. For this reason, the Distribution reports are identical.
12.
In the Process Capability report, right-click the Expected Overall % column in the Nonconformance report and select Simulate.
13.
Next to Number of Samples, enter 500.
14.
(Optional) Next to Random Seed, enter 12345.
15.
The calculation might take several seconds. A data table entitled Process Capability Simulate Results (Expected Overall %) appears. Because Purity has only a lower specification limit, the Below LSL values are identical to the Total Outside values.
Distribution of Simulated Total Outside Values for Purity

Help created on 9/19/2017