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Common and Special Causes of Variation

Walter Shewhart

In the 1920's Walter Shewhart developed the idea of the control chart to help decide when the output of a process was part of "a stable system of chance causes", or whether there was an "assignable cause". Shewhart viewed a stable system as one whose variation arose as the result of many small perturbations (which we call common cause variation); for a stable process the observations could be described by a probability distribution - the system is said to be "in a state of statistical control", or simply, in control. An unusually large deviation suggested that the system had been disturbed and hence there was an assignable cause for the disturbance - the system is out of control, or unstable.

W. Edwards Deming

Deming substituted the term special cause for assignable cause. Deming said that uncovering special causes was the responsibility of the local work force (those who had day-to-day contact with the process). Common causes were part of the system. The system is the responsibility of management. If the common cause variation is too large, it is the responsibility of management to change the system. Deming, stated that 85% of the problems with processes were system problems; later he increased this to over 94%, based on his own experience.

Some authors regard this sharp delineation between special causes and common causes, workforce responsibility and management responsibility, as overly simplistic. For example, when a special cause is signalled, and its cause found (rarely an easy task), the local workforce may not have the authority to fix up the problem. Nevertheless, the distinction between special and common causes of variability is a useful one, and the recognition of responsibility assignments to the workforce for sporadic problems and to management for system problems is generally sound.
Here are some examples of common and special causes of variation.

Common Causes

  • Inappropriate procedures.
  • Poor design.
  • Poor maintenance of machines.
  • Lack of clearly defined standard operating procedures.
  • Poor working conditions,
    e.g. lighting, noise, dirt, temperature, ventilation.
  • Machines not suited to the job.
  • Substandard raw materials.
  • Measurement error.
  • Vibration in industrial processes.
  • Ambient temperature and humidity.
  • Insufficient training.
  • Normal wear and tear.
  • Variability in settings.
  • Computer response time.

Special Causes

  • Operator absent.
  • Poor adjustment of equipment.
  • Operator falls asleep.
  • Faulty controllers.
  • Machine malfunction.
  • Computer crashes.
  • Poor batch of raw material.
  • Power surges.

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