SPC is an improvement system which uses statistical techniques to understand and reduce process variation.
It is the most effective way to achieve defect prevention and to support process and Continuous improvement.

What does “SPC” mean

The use of statistics to analyse a process or output, so that actions can be taken to achieve and maintain statistical control and to improve the process.

  • Statistical: drawing conclusions using a scientific approach to collecting and analysing data.
  • Process: the combination of people, equipment, materials, methods and environment working together to produce an output; any work area that has identifiable, measurable output(s).
  • Control: to make something behave in a predictable, consistent manner.

Concept of Variation in SPC

No two things are exactly alike. The differences between them may be large, or they may be small. Sometimes the differences can be measured (variables data) and sometimes they can be counted (attributes data), but they are always present.

There are seven concepts about variation that everyone should know:

  1. All variation is caused by something. There are reasons why your weight goes up and down, why Sales go up and down, why output from a production process varies.
  2. There are four types of variation:
    1. Common Cause Variation: Many sources of chance variation are always present in any process (e.g. inputs, conditions, etc.) that contribute in varying degrees to relatively small, apparently random shifts in outcomes. A process containing only common cause variation will form a pattern that is stable over time, is predictable and provides a basis for subsequent improvement.
    2. Special Cause Variation: Special causes intermittently induce variation over and above the variation natural in the system (common causes). Special cause variation appears as an extreme point or an identifiable pattern in data.
    3. Tampering: Tampering is additional variation caused by unnecessary adjustments made to try to compensate for common cause variation.
    4. Structural Variation: Structural variation is regular, systematic changes in output, e.g. seasonal patterns, long-term trends, and multiple process streams.
  1. Distinguishing between the four types of variation is critical because the management action required for each type is different.
  2. The strategy for special causes is: get timely data. When the data indicate a special cause is present, investigate immediately. Find out what was different about that point.
  3. The strategy for improving a common cause system is more difficult. In a common cause situation, all the data are relevant, not just the most recent data point. In depth knowledge of the process to be improved is essential when only common causes are present. This knowledge is obtained by using the basic statistical tools as part of a Continual Improvement Strategy.
  1. When all the variation is due to common causes, the result is a stable system, which is said to be in statistical control.
  2. The amount of system variation present is calculated from the process data. Control limits describe the range of variation expected in the process due to the combined effect of the common causes.

The seven fundamental concepts described above provide the basis for the continual improvement strategy

If you are interested in Statistical Process Control (SPC) and getting it implemented in your organisation, then our SPC Training might be interesting for you.

Alternatively you can continue to our quality training page for an overview of the training we provide.

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SPC Control Chart