Control charting is a tool used to monitor processes and to assure that they remain in control or stable. Proposed by Walter Shewart in 1924, control charts help distinguish process variation due to assignable causes from those due to unassignable causes.

Table 1: Types of Process Variation Found on a Control Chart
Types of Variation Variation Characteristics
Assignable cause, also known as special cause
  • Meaningful factors of process; not always present
  • Cause can be avoided and should be investigated
  • Not normal to process
Unassignable cause, also known as common cause or chance cause
  • Factor caused by chance; always present
  • Unavoidable and inherent in a process
  • Normal and expected within process

Elements of a Control Chart

A control chart consists of:

  1. A central line,
  2. An upper control limit,
  3. A lower control limit, and
  4. Process values plotted on the chart.

If all process values are plotted within the upper and lower control limits and no particular tendency is noted, the process is referred to as in control. If the process values are plotted outside the control limits or show a particular tendency, however, the process is referred to as out of control (see red-circled data points in Figure 2 below).

Figure 1: In Control Process Control Chart
Figure 1: In Control Process Control Chart
Figure 2: Out of Control Process Control Chart
Figure 2: Out of Control Process Control Chart

There are many types of control charts. In a future article, we will investigate the different types of control charts by process values and purpose.

In a control chart, control limits are calculated by the following formula:

(average process value) (3 x standard deviation)

where the standard deviation is due to unassigned process variation only.

Constructing a Control Chart

Here is the general process for making or constructing a control chart for your process:

  1. Select the process you would like to chart
  2. Determine your process sampling plan
  3. Collect data from your process
  4. Calculate the control chart specific statistics
  5. Calculate your control limits
  6. Construct your control chart
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