Capability analysis preferences

Users with engineer privileges can specify default preferences for all capability analyses.

In This Topic

Shared preferences
Normal capability analyses
Between/within capability analyses

Select Analysis Preferences

in the Engineering portal, then navigate to capability analysis settings.

Note

These preferences are the initial settings for all capability analyses. To change settings by measure, go to Specify capability settings for each measure.

Shared preferences

Specify the tolerance and display preferences that are shared across the capability analyses.

Tolerance

Enter the width of the tolerance in number of standard deviations (σ). By default, the tolerance is 6 standard deviations wide (3 standard deviations on each side of the process mean).

The K value represents the width of a two-sided tolerance. If you want to use a one-sided tolerance, enter a two-sided tolerance value that is twice that of the one-sided tolerance. For example, if you want to use a one-sided tolerance of 3σ, enter 6.

Display performance metrics

Select how you want to display the expected and observed out-of-specification values.

Parts per million: Display the values in parts per million (PPM).
Percents: Display the values as percentages.

Display capability metrics

Select the measures of capability to display.

Capability statistics (Cp, Pp): Calculate and display capability indices, such as Cp and Pp.
Benchmark Z's (σ level): Calculate and display Z.bench values. The choice to use Z.bench often depends on company or industry practices.

Normal capability analyses

Estimation method for within-subgroup standard deviation (subgroup size > 1)

Select a method to estimate the within–subgroup standard deviation when the subgroup size is larger than 1.

Pooled standard deviation: The pooled standard deviation is the weighted average of subgroup variances, which gives larger subgroups more influence on the overall estimate. This method provides the most precise estimate of standard deviation when the process is in control.
Rbar: Rbar is the average of the subgroup ranges. This method is a common estimate of the standard deviation and works best with subgroup sizes from 2 to 8.
Sbar: Sbar is the average of the subgroup standard deviations. This method provides a more precise estimate of the standard deviation than Rbar, especially with subgroup sizes > 8.

Estimation method for within-subgroup standard deviation (subgroup size = 1)

Select a method to estimate the within–subgroup standard deviation when the subgroup size equals 1.

Average moving range: The average moving range is the average value of the moving range of two or more consecutive points. This method is commonly used when the subgroup size is 1.
Median moving range: The median moving range is the median value of the moving range of two or more consecutive points. This method is best to use when data have extreme ranges that could influence the moving range.
Square root of MSSD: The square root of MSSD is the square root of the mean of the squared differences between consecutive points. Use this method when you cannot reasonably assume that at least 2 consecutive points were collected under similar conditions.

Length of moving range

Enter the number of observations used to calculate the moving range. The length must be ≤ 100. The default length is 2 because consecutive values have the greatest chance of being alike.

Use unbiasing constants: Unbiasing constants reduce the bias that can occur when a parameter is estimated from a small number of observations. As the number of observations increases, unbiasing constants have less effect on the calculated results.

Note
Often, the choice to use unbiasing constants depends on company policy or industry standards.

Between/within capability analyses

Estimation method for within-subgroup standard deviation

Select a method to estimate the within–subgroup standard deviation.

Pooled standard deviation: The pooled standard deviation is the weighted average of subgroup variances, which gives larger subgroups more influence on the overall estimate. This method provides the most precise estimate of standard deviation when the process is in control.
Rbar: Rbar is the average of the subgroup ranges. This method is a common estimate of the standard deviation and works best with subgroup sizes from 2 to 8.
Sbar: Sbar is the average of the subgroup standard deviations. This method provides a more precise estimate of the standard deviation than Rbar, especially with subgroup sizes > 8.

Estimation method for between-subgroup standard deviation

Select a method to estimate the between–subgroup standard deviation.

Average moving range: The average moving range is the average value of the moving range of two or more consecutive points. This method is commonly used when the subgroup size is 1.
Median moving range: The median moving range is the median value of the moving range of two or more consecutive points. This method is best to use when data have extreme ranges that could influence the moving range.
Square root of MSSD: The square root of MSSD is the square root of the mean of the squared differences between consecutive points. Use this method when you cannot reasonably assume that at least 2 consecutive points were collected under similar conditions.

Length of moving range

Enter the number of observations used to calculate the moving range. The length must be ≤ 100. The default length is 2 because consecutive values have the greatest chance of being alike.

Use unbiasing constants: Unbiasing constants reduce the bias that can occur when a parameter is estimated from a small number of observations. As the number of observations increases, unbiasing constants have less effect on the calculated results.

Note
Often, the choice to use unbiasing constants depends on company policy or industry standards.