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Statistical Process Control

Statistical process control (SPC) procedures can help you monitor process behavior.

Arguably the most successful SPC tool is the control chart, originally developed by Walter Shewhart in the early 1920s. A control chart helps you record data and lets you see when an unusual event, e.g., a very high or low observation compared with “typical” process performance, occurs.

Control charts attempt to distinguish between two types of process variation:

  • Common cause variation, which is intrinsic to the process and will always be present.
  • Special cause variation, which stems from external sources and indicates that the process is out of statistical control.

Various tests can help determine when an out-of-control event has occurred. However, as more tests are employed, the probability of a false alarm also increases.


A marked increase in the use of control charts occurred during World War II in the United States to ensure the quality of munitions and other strategically important products. The use of SPC diminished somewhat after the war, though was subsequently taken up with great effect in Japan and continues to the present day. (For more, see The History of Quality)

Many SPC techniques have been “rediscovered” by American firms in recent years, especially as a component of quality improvement initiatives like Six Sigma. The widespread use of control charting procedures has been greatly assisted by statistical software packages and ever-more sophisticated data collection systems.

Over time, other process-monitoring tools have been developed, including:

  • Cumulative Sum (CUSUM) charts: the ordinate of each plotted point represents the algebraic sum of the previous ordinate and the most recent deviations from the target.
  • Exponentially Weighted Moving Average (EWMA) charts: each chart point represents the weighted average of current and all previous subgroup values, giving more weight to recent process history and decreasing weights for older data.

More recently, others have advocated integrating SPC with Engineering Process Control (EPC) tools, which regularly change process inputs to improve performance.

Contributed by Keith M. Bower, a statistician and webmaster of

Tutorial: Statistical Quality Control Versus Statistical Process Control

Control Chart Template (Excel, 973 KB)

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