Each point on a Laney P' chart represents the proportion of defective items or units for one subgroup.
If the process is in control, the points vary randomly around the center line, and the process exhibits only common-cause variation. Investigate points that fall outside the control limits or that exhibit nonrandom patterns for possible special-cause variation.
The center line on a Laney P' chart represents the average proportion of defective units for the process. The average proportion of defective units is also called the process proportion.
Use the center line to observe how the process performs compared to the average. If the process is in control, then the points vary randomly around the center line.
Do not confuse the center line with the target value for your process. The target is your desired outcome. The center line is the actual outcome.
Do not confuse control limits with specification limits. Specification limits represent customer requirements and indicate the amount of variation that you want to see in the process. Control limits represent the actual amount of variation that is in the sample data. A process can be in control, yet not be capable of meeting specifications.
Sigma Z measures overdispersion or underdispersion in your data.
For example, the following graphs show a traditional P chart and a Laney P' chart of the same data. The subgroups are large and the data exhibit overdispersion.
The tests for special causes assess whether the plotted points are randomly distributed within the control limits.
Use the tests for special causes to determine which observations you may need to investigate and to identify specific patterns and trends in your data. Each of the tests for special causes detects a specific pattern or trend in your data, which reveals a different aspect of process instability. For example, Test 1 detects a single out-of-control point. Test 2 detects a possible shift in the process.
Four tests are available with this control chart.
Use stages to create a historical control chart that shows how a process changes over specific periods of time. By default, Minitab recalculates the center line and control limits for each stage. For more information, go to Add stages to show how a process changed.
This historical control chart shows three stages of a process, which represent before, during, and after the implementation of a new procedure.