If only common causes of variation are present in a process, then the output of the process forms a distribution that is stable over time and is predictable. If special causes of variation are present, the process output is not stable over time. Note, the process may also be unstable if either the process average or variation is out-of-control.
Common Causes: of variation refer to the many sources of variation within a process that has a stable and repeatable distribution over time. This is called a state of statistical control and the output of the process is predictable.
Special causes: refer to any factors causing variation that are not always acting on the process.
If special causes of variation are present, the process distribution changes and the process; output is not stable overtime. When plotting a process on a control chart, lack of process stability can be shown by several types of patterns including: points outside the control limits, trends, points on one side of the center line, cycles, etc.
Attribute and Discrete Capability
The control chart represents the process capability, once special causes have been identified and removed from the process. For attribute charts, capability is defined as the average proportion or rate of non-conforming product.
For p charts, the process capability is the process average non-conforming, and is preferably based on 25 or more in-control periods. If desired, the proportion conforming to specification 1 - p, may be used.
For np charts, the process capability is the process average nonconforming p, and is preferably based on 25 or more in-control periods. For c charts, the process capability is the average number of nonconformities, c, in a sample of fixed size n.
For u charts, the process capability is the average number of nonconformities per reporting unit, u.
The average proportion of nonconformities may be reported on a defects per million opportunities scale by multiplying p times 1,000,000.