If the system fails any of the tests for control, it is out-of-control or unstable.
If your system is unstable, does the special cause of variation create a favorable output? Does it improve the process? If yes, find the special cause(s) of variation. Try to replicate it and incorporate it into the process.
If not, and it creates a negative output or hurts the process, find the special cause(s) of variation and take steps to eliminate it. After you remove special causes of variation, continue collecting, charting, and analyzing the data. Once the process has been stabilized, consider performing capability analysis to compare how the process is running in relation to its specifications.
If it does not fail any of the tests for control, the process is stable.
If your process is stable, is the data normal distributed? Is it capable of producing output that is within specifications? You may want to create a histogram and perform capability analysis to learn more about your process.
If the process is stable, but failing to meet specification requirements, look for the source(s) of common cause variation. Can these be eliminated or reduced? How can the system be improved?
Note: A process that is currently stable, may not remain stable indefinitely. A new batch of raw material, a new operator, or new equipment, can change the output. Therefore, you should continue collecting, charting, and analyzing data for stable processes.
Capability analysis can be done using software products such as SQCpack.
>> Analyze for special cause variation
>> When do you recalculate control limits
>> What do the chart pairs mean (variables control charts only)