Select the analysis options for Normal Capability Analysis for Multiple Variables

Stat > Quality Tools > Capability Analysis > Multiple Variables (Normal) > Options

Targets (Display Cpm)

To specify target values for your process variables, enter one value, multiple values, or a column of values. If you enter one value, it applies to all variables or groups. If you enter multiple values or a column of values, the values correspond sequentially to the columns that you entered in Variables or to the groups in the By variables column.

When you enter a target, Minitab calculates Cpm, a capability index that also considers how much the data deviate from the target.

Use tolerance of K × σ for capability statistics

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).

You can enter one value, multiple values, or a column of values. If you enter one value, it applies to all variables or groups. If you enter multiple values or a column of values, the values correspond sequentially to the columns that you entered in Variables or to the groups in the By variables column.

Minitab interprets the K value as 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.

Note

If you want the tolerance value that you enter to be the default setting for every capability analysis that you perform, choose Tools > Options > Control Charts and Quality Tools > Capability Analysis and enter the default tolerance.

Perform Analysis

By default, Minitab performs both within or between/within capability analysis and overall capability analysis. If you don't want to perform one of the analyses, deselect that checkbox.

Within or between/within subgroup analysis
Perform the between/within subgroup analysis, which assesses the variation both within and across subgroups. This analysis estimates how well your process could perform if additional sources of systemic variation, besides the variation between and within the subgroups, could be eliminated.
Overall analysis
Perform the overall analysis, which indicates the actual capability of your process. This analysis estimates what your customer actually experiences over time.

Display

Select the measures of capability that you want Minitab to display:
  • Capability stats (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.
Note

If you want to display benchmark Z's by default whenever you perform a capability analysis, choose Tools > Options > Control Charts and Quality Tools > Capability Analysis and change the default display setting.

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.
Include confidence intervals
Select to display confidence intervals for the capability indices.
Confidence level
Enter a confidence level between 0 and 100. Usually, a confidence level of 95% works well. A 95% confidence level indicates that if you took 100 random samples from the process, you could expect approximately 95 of the samples to produce confidence intervals that contain the actual value of the capability index for the process (if all the process data could be collected and analyzed).
For a given set of data, a lower confidence level produces a narrower confidence interval, and a higher confidence level produces a wider confidence interval. The width of the interval also tends to decrease with larger sample sizes. Therefore, you may want to use a confidence level other than 95%, depending on your sample size, as follows:
  • If your sample size is small, a 95% confidence interval may be too wide to be useful. Using a lower confidence level, such as 90%, will produce a narrower interval. However, the likelihood that the interval contains the capability index for the process decreases.
  • If your sample size is large, you may want to consider using a higher confidence level, such as 99%. With a large sample, a 99% confidence level may still produce a reasonably narrow interval while increasing the likelihood that the interval contains the capability index for the process.
Confidence intervals
Select the type of confidence interval or bound that you want to display:
  • Two-sided: Display a confidence interval that has both a lower and an upper confidence bound.
  • Lower bound: Display only a lower confidence bound. You might want to display only a lower bound if you need to assess only whether a capability index is likely to be greater than a specified value.
  • Upper bound: Display only an upper bound. You might want to display only an upper bound if you need to assess only whether a capability index is likely to be less than a specified value.
By using this site you agree to the use of cookies for analytics and personalized content.  Read our policy