Learn more about Statistics Toolbox

Control Charts

A control chart displays measurements of process samples over time. The measurements are plotted together with user-defined specification limits and process-defined control limits. The process can then be compared with its specifications—to see if it is in control or out of control.

The chart is just a monitoring tool. Control activity might occur if the chart indicates an undesirable, systematic change in the process. The control chart is used to discover the variation, so that the process can be adjusted to reduce it.

Control charts are created with the controlchart function. Any of the following chart types may be specified:

• Xbar or mean

• Standard deviation

• Range

• Exponentially weighted moving average

• Individual observation

• Moving range of individual observations

• Moving average of individual observations

• Proportion defective

• Number of defectives

• Defects per unit

• Count of defects

Control rules are specified with the controlrules function.

For example, the following commands create an xbar chart, using the "Western Electric 2" rule (2 of 3 points at least 2 standard errors above the center line) to mark out of control measurements:

load parts;
st = controlchart(runout,'rules','we2');
x = st.mean;
cl = st.mu;
se = st.sigma./sqrt(st.n);
hold on
plot(cl+2*se,'m')

Measurements that violate the control rule can then be identified:

R = controlrules('we2',x,cl,se);
I = find(R)
I = 
   21
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   27 

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