Overview for Nonnormal Capability Sixpack

Use Nonnormal Capability Sixpack to assess the assumptions for nonnormal capability analysis and evaluate only the major indices of overall capability. Using this analysis, you can do the following:

  • Determine whether the process is stable and in control
  • Determine whether the data follow a specific nonnormal distribution
  • Estimate overall capability (Pp, Ppk)

To perform the analysis, you must specify a lower or upper specification limit (or both) to define your process requirements. You must also select a nonnormal distribution to model your data. The analysis evaluates the spread of the process data in relation to the specification limits. When a process is capable, the process spread is smaller than the specification spread. This analysis also estimates the proportion of product that does not meet specifications.

For example, administrators at a medical center want to evaluate wait times for patients with scheduled medical appointments. They want to ensure that patients are seen by a physician within 15 minutes of their scheduled appointment time. The administrators fit a Weibull distribution to the process data to analyze its capability.

Where to find this analysis

To perform nonnormal capability sixpack, choose Stat > Quality Tools > Capability Sixpack > Nonnormal.

When to use an alternate analysis

  • If you do not know which nonnormal distribution best fits your data, use Individual Distribution Identification before you perform this analysis.

  • If you want to evaluate a more complete set of capability measures, in addition to the major indices, use Nonnormal Capability Analysis.

  • If you want to check the assumptions for evaluating the capability of your process based on a normal distribution, after transforming nonnormal data, use Normal Capability Sixpack.

  • If your process produces large variation between subgroups, such as a batch process, use Between/Within Capability Sixpack to assess the assumptions for a between/within capability analysis.