Process Capability Platform Overview

The Process Capability platform provides the tools needed to measure the compliance of a process to given specifications. By default, JMP shows a goal plot and capability box plot for each variable in the analysis. You can add normalized box plots, summary tables, capability indices, and an individual report for each variable in the analysis. You can supply specification limits in several ways:

•	in the data table, using a column property

•	by requesting the Spec Limits Dialog in the launch window

•	by loading the limits from a specification limits data table.

You can specify two-sided, one-sided, or asymmetric specification limits.

A capability index is a ratio that relates the ability of a process to produce product that meets specification limits. The index relates estimates of the mean and standard deviation of the quality characteristic to the specification limits. The mean and standard deviation are well-defined only if the process is stable.

The conclusions drawn from the capability indices presented in the Process Capability platform are based on the following assumptions:

•	The quality characteristic is stable (in statistical control).

•	The distribution of the quality characteristic is normal.

Note: Process Capability analysis for individual responses is accessible through Analyze > Quality and Process > Control Chart Builder.

You should also note that capability indices constructed from small samples can be highly variable. The Process Capability platform provides confidence intervals for all capability indices. Use these to determine the range of potential values for your quality characteristic’s actual capability.

Guidelines for values of capability indices can be found in Montgomery (2013). The minimum recommended value is 1.33. Six Sigma initiatives aim for much higher capability levels that correspond to extremely low rates of defective parts per million.

Capability indices in the Process Capability platform are computed using both the overall (long-term) variation and the within subgroup (short-term) variation. If the process is stable, these two measures of variation should yield similar results since the overall and within subgroup variation should be similar. You can specify subgroups in the launch window. The normalized box plots and summary tables can be calculated using either the overall or the within sigma variation. See Additional Examples of the Process Capability Platform for examples of capability indices computed for stable and unstable processes.

You can specify within-subgroup (short-term) estimates in several ways. You can specify a column that defines subgroups or you can select a constant subgroup size. For each of these methods, you can choose to estimate the process variation using the average of the unbiased standard deviations or using the average of the ranges. If you do not specify subgroups, the Process Capability platform constructs a within-subgroup estimate of the process variation using a moving range of subgroups of size two. Finally, you can specify a historical sigma to be used as an estimate of the process standard deviation.

The individual detail reports include indices that help demonstrate a system’s ability to meet a set of requirements. Capability indices help change the focus from just meeting qualifications to continuous improvement of a process. The Process Capability platform reports two sets of capability indices:

•	Cpk, Cpl, Cpu, Cp, and Cpm. These indices are based on a within-subgroup (short-term) estimate of the process standard deviation.

•	Ppk, Ppl, Ppu, Pp, and Cpm. These indices are based on an overall (long-term) estimate of the process standard deviation. Note that the process standard deviation does not exist if the process is not stable. See Montgomery (2013).

See Capability Indices for details about the calculation of the capability indices.

A platform preference enables you to change the reporting to Cp notation only.

Note: The Process Capability platform expands significantly on the Capability analyses that are available through Analyze > Distribution and through Analyze > Quality and Process > Control Chart. By default, the Process Capability platform uses the appropriate AIAG notation for capability indices. It denotes an index constructed from an overall variation estimate using Ppk labeling. The previous Capability platform reported only overall variation with Cpk or Ppk labeling based on a platform preference. In the new platform, Cpk corresponds to within variation and Ppk corresponds to overall variation.

For more information about process capability analysis, see Montgomery (2013) and Wheeler (2004).