Statistical Process Control

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What is SPC?

Statistical process control (SPC) is a method of quality control which employs statistical methods to monitor and control a process. This helps to ensure that the process operates efficiently, producing more specification-conforming products with less waste, rework or scrap. SPC can be applied to any process where the “conforming product” output can be measured.

The application of SPC involves three main phases of activity:

  1. Understanding the process and the specification limits.
  2. Eliminating special sources of variation, so that the process is stable.
  3. Monitoring the ongoing production process using control charts, to detect significant changes of mean or variation.

Control charts

A control chart is a type of trend chart with limits specifically used to track an ongoing process to see if it is within limits or in control i.e. if the variation is natural and to be expected (chance variation), or if it due to special causes.  Hence, when a process goes outside of a control limit, it is not necessarily a cause to alarm.  Consistent crossing of control limits, however, indicates that the process variation is not simply due to chance.

Control charts vary slightly depending on what kind of data variation is being examined, though basically they all look much the same.

Image source: Wikipedia

The X axis tracks time and the Y axis charts the factor being studied.  The average or mean of the process is indicated and limits are added above and below the average.  These limits can be derived in at least two different ways:

  1. Through experience and judgement; these are called action limits, or
  2. By statistically deriving true control limits from actual historic data.

Stable processes

When the process does not trigger any of the control chart “detection rules” for the control chart, it is said to be stable. Only when a process is stable, can it be improved.

For an example of how to use Excel to create a basic control chart with upper and lower control limits go to this YouTube video .

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