The following example illustrates constructing a control chart for data that are not sub-grouped. The data are measurements on a steam turbine engine. For an example that uses sub-grouped data, Example of Monitoring a Process Using Sub-Grouped Data.
|
1.
|
|
2.
|
Select Analyze > Quality and Process > Control Chart > Multivariate Control Chart.
|
|
3.
|
Select all of the columns and click Y, Columns.
|
|
4.
|
Click OK.
|
Figure 6.2 Initial Multivariate Control Chart
|
1.
|
From the red triangle menu, select Save Target Statistics.
|
Figure 6.3 Target Statistics for Steam Turbine Data
|
2.
|
Save the new data table as Steam Turbine Targets.jmp.
|
|
1.
|
|
2.
|
Select Analyze > Quality and Process > Control Chart > Multivariate Control Chart.
|
|
3.
|
Select all of the columns and click Y, Columns.
|
|
4.
|
Click Get Targets.
|
|
5.
|
Open the Steam Turbine Targets.jmp table that you saved.
|
|
6.
|
Click OK.
|
|
7.
|
From the red triangle menu, select Set Alpha Level > Other.
|
|
8.
|
Figure 6.4 Steam Turbine Control Chart
Figure 6.4 shows out-of-control conditions occurring at observations 2, 3, 4, 5, and 8. This result implies that these observations do not conform to the historical data from Steam Turbine Historical.jmp, and that the process should be further investigated. To find an assignable cause, you might want to examine individual univariate control charts or perform another univariate procedure.