There is also Variable 2 Sample Capability Analysis available (Before vs After capability comparison) as a separate document. It works very much the same way as this guide, so it is recommended you also use this guide when completing the 2 Sample statistics document. Note: 2 Sample does not contain Capability Sixpack but does contain all other tabs.
Open the file titled Variable Capability Analysis, and once open, ensure that the Data Entry tab is selected.
Figure 23 – Variable Capability Analysis Data Input
- USL: Upper specification limit for your process / data set. At least 1 specification limit must be entered.
- LSL: Lower specification limit for your process / data set. At least 1 specification limit must be entered.
- Target: Select a target value for your process. This can be the same as 1 of the specification limits or in between.
- Title of Data: Enter a title to appear at the top of your capability analysis for easy identification.
- Data: On the right this represents the data of the process being analysed.
Click on the Capability Sixpack tab at the bottom of the sheet (Not included in 2 Sample Variable Capability Analysis / Before vs After Capability comparison).
Figure 24 – Variable Capability Sixpack
The sixpack is a good general summary sheet for any variable capability analysis. The layout will be:
Sample size check
Individual Value Chart / Xbar Chart
Moving Range Chart
Last 25 Observations
Statistical Information and Guidance Panel
Once the data has been entered, select the Process Capability tab at the bottom of the sheet.
Figure 25 – Variable Capability Analysis Histogram
The histogram for capability above will show the distribution of data, including the upper and lower specification limits along with the target line, and unlike the Binomial Capability Analysis Histogram, this will show the “bell shaped curve” of the data,
To the right of the chart itself, the statistical data is displayed along with a set of guidelines on Cp & Cpk, Kurtosis and Skewness values.
CESP selects an optimal bin size and number of bins from multiple methods (Sturges, Freedman, Sqrt). You can override the number of Histogram bins if you so wish by entering a value in the top right yellow box. Deleting this value will revert back to optimal selection.
Click on the Control Charts tab at the lower edge of the sheet.
Figure 26 – Variable Capability Analysis Control Charts
This will be split between 2 types of chart. If the subgroup size set on data entry was 1, this will show the IM-R chart (as per the example above) but if it is set to anything other than 1, the system will revert to generating the X-Bar R Chart instead.
Between the charts, a set of Nelson’s Rules Tests appear, showing the overall result.
A text description statement is provided at the lower section of the charts stating whether the process is in or out of statistical control. If it is out of statistical control, the Nelsons Rules Error Lookup grid to the upper right of the main charts will show which data points have breached Nelson’s Rules, and which rules test they have breached.
You can then refer to the Error Lookup section (at the bottom) for extra details on the data points indicating infringements to the Nelson rules.
Figure 27 – Error Lookup – Nelson’s Rules Breaches
This will indicate a FAIL next to each data point and what Nelson rules it infringes.
Full training regarding Nelson’s Rules will be provided by your Capella trainer in formal training sessions.
Click on the Normality Plot tab at the bottom of the sheet.
Figure 28 – Variable Capability Analysis Normality Plot
The normality plot will provide information regarding the normal distribution of the data, and provides the numerical value for both the Anderson-Darling test (AD Value), the p-Value, and provides the result of the Rejection of Null Hypothesis Test.