The Xbar chart plots the average of the measurements within each subgroup. The center line is the average of all subgroup averages. The control limits, which are set at a distance of 3 standard deviations above and below the center line, show the amount of variation that is expected in the subgroup averages.
Minitab displays an Xbar chart when your subgroup size is greater than 1.
Use an Xbar chart to monitor the mean of a process and determine whether it is stable enough to perform capability analysis.
The I chart plots individual observations. The center line is an estimate of the process average. The control limits, which are set at a distance of 3 standard deviations above and below the center line, show the amount of variation that is expected in the individual sample values.
Minitab displays an I chart when your subgroup size is 1.
Use an I chart to assess whether the individual measurements are in control and determine whether the process is stable enough to perform capability analysis.
Red points indicate observations that fail at least one of the tests for special causes and are not in control. Out-of-control points indicate that the process may not be stable and that the results of a capability analysis may not be reliable. You should identify the cause of out-of-control points and eliminate special-cause variation before you analyze process capability.
The R chart plots the subgroup ranges. If the subgroup size is constant, then the center line is the average of all subgroup ranges. If the subgroup sizes differ, then the value of the center line depends on the subgroup size, because larger subgroups tend to have larger ranges. The control limits, which are set at a distance of 3 standard deviations above and below the center line, show the amount of variation that is expected in the subgroup ranges.
Minitab displays an R chart to monitor variation if your subgroup size is greater than 2 but less than 9.
Use an R chart to monitor the variation of a process and determine whether it is stable enough to perform capability analysis. The R chart indicates whether the subgroup-to-subgroup variation is in control.
The S chart plots the subgroup standard deviations. The center line is the average of all subgroup standard deviations. The control limits, which are set at a distance of 3 standard deviations above and below the center line, show the amount of variation that is expected in the subgroup standard deviations.
Minitab displays an S chart to monitor variation if your subgroup size is greater than or equal to 9.
Use an S chart to monitor the variation (standard deviation) of your process and determine whether it is stable enough to perform capability analysis. The S chart indicates whether the subgroup-to-subgroup variation is in control.
The MR chart plots the moving ranges for consecutive observations. The center line is the average of all moving ranges. The control limits, which are set at a distance of 3 standard deviations above and below the center line, show the amount of variation that is expected in the moving ranges.
Minitab displays an MR chart If your subgroup size is 1.
Use an MR chart to monitor the variation (moving range) of your process and to determine whether it is stable enough to perform capability analysis. The MR chart indicates whether the variation from observation to observation is in control.
Red points indicate observations that fail at least one of the tests for special causes and are not in control. Out-of-control points indicate that the process may not be stable and that the results of a capability analysis may not be reliable. You should identify the cause of out-of-control points and eliminate special-cause variation before you analyze process capability.
The tests for special causes assess whether the plotted points on each control chart 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.
The Last 25 Subgroups plot shows the data points for each of the last 25 subgroups and displays a line for the overall process mean.
Use the Last 25 Subgroups plot to evaluate whether the distribution of the observations within the subgroups meets the requirements for your capability analysis.
If the plot shows evidence of problems or changes across subgroups, the capability results may not be valid. Investigate your process to determine why the data values are not distributed randomly across the subgroups.
If the subgroup size is 1, Minitab displays a Last 25 Observations plot, which is interpreted similarly.
The capability histogram shows the distribution of your sample data. Each bar on the histogram represents the frequency of data within an interval.
Use the capability histogram to visualize your sample data in relation to the distribution fit and the specification limits.
To visually assess the distribution fit, compare the bars in the histogram with the curved fit line. The shape of the data in the histogram should approximately match the curve. To ascertain whether the data follow the distribution, use the results in the probability plot.
To determine the number of nonconforming items in your process, use the overall PPM result.
Use the normal probability plot to assess the requirement that your data follow a normal distribution.
If the normal distribution is a good fit for the data, the points form an approximately straight line and fall along the fitted line that is located between the confidence bounds. Departures from this straight line indicate departures from normality. If the p-value is greater than 0.05, you can assume that the data follow the normal distribution. You can evaluate the capability of your process using a normal distribution.
If the p-value is less than 0.05, your data are not normal and the capability analysis results may not be accurate. Use Individual Distribution Identification to determine whether you must transform the data or fit a nonnormal distribution to perform the capability analysis.
The capability plot is located at the lower right corner of the Normal Capability Sixpack Report.
The capability plot consists of three intervals:
The process center is shown by the tick mark inside the Overall and Within process spread intervals. The target, if you have one, is shown by the tick mark inside the specification spread (Specs).
Use the capability plot to visually assess the capability of your process.
To assess the potential capability of your process, compare the within process spread with the specification spread. To assess the overall capability of your process, compare the overall process spread with the specification spread. If the process spread is greater than the specification spread, your process needs improvement.
Compare the process center to the target, if you have one. If the process is centered (on target), the middle tick marks for the specifications and for the process spread are vertically aligned. If the process is not centered, investigate the reasons why.
If the within process spread and the overall process spread differ greatly, your process may not be stable. Check the control charts to ensure that your process is in control.