To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.
If your data are counts of defectives or defects, use an attribute control chart, such as P Chart or U Chart.
Because control charts detect changes over time, the order of the data is important. You should enter the data in the order it was collected, with the oldest data at the top of the worksheet.
Collect data at equally spaced time intervals, such as every hour, every shift, or every day. Select a time interval that is short enough that you can identify changes to the process soon after the changes occur.
If you can collect data in subgroups, use Xbar Chart.
If you have fewer than the recommended number of observations, then you can still use the control chart, but the results are preliminary because the control limits may not be precise. If you use the chart regularly, re-estimate the standard deviation and the control limits after you collect the recommended number of observations.
If the process variation is not stable, the control limits may not adequately reflect the control status of the process.
If the data are very skewed, you could try a Box-Cox transformation to see if that corrects the nonnormal condition. If your process naturally produces nonnormal data and the transformation is effective, you can use the chart of the transformed data to assess the stability of your process.
If consecutive data points are correlated, the control limits will be too narrow and you may see a large number of false out-of-control signals.