How to Create a Control Chart

8/13/2019 How to Create a Control Chart

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How to Create a Control ChartSample Control ChartsEdited by Kimberly Eng, Nathan Wong, Tom Viren, Brandywine and 9 others

Control charts are an efficient way of analyzing performance data to evaluate a

process. Control charts have many uses; they can be used in manufacturing to

test if machinery are producing products within specifications. Also, they have

many simple applications such as professors using them to evaluate tests scores.

To create a control chart, it is helpful to have Excel; it will simplify your life.

EditSteps

1. 1Check to see that your data meets the following criteria:

Data should usually be normally distributed revolving around a mean (average). In the example below, a bottle company fills their bottles to 16 oz. (mean);

they are evaluating if their process is in-control. The amount in ounces

over 16 oz. is normally distributed around the mean.

Measurements need to be independent of one another. In the example, the measurements are in subgroups. The data in the

subgroups should be independent of the measurement number; each data

point will have a subgroup and a measurement number.
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2.

2Find the mean of each subgroup.
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To find the mean, add all measurements in the subgroup and divide by the numberof measurements in the subgroup.

In the example, there are 20 subgroups and in each subgroup there are 4measurements.

3. 3Find the mean of all of the means from the previous step (X).


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This will give you the overall mean of all the data points. The overall mean will be the centerline in the graph (CL), which is 13.75 for our

example.

4. 4Calculate the standard deviation (S) of the data points (see tips).

5. 5Calculate the upper and lower control limits (UCL, LCL) using the following

formula:

UCL = CL + 3*S

LCL = CL3*S

The formula represents 3 standard deviations above and 3 standard deviations below the

mean respectively.


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6. 6Refer to the below chart with steps 7 through 10.


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7. 7Draw a line at each deviation.

In the above example, there is a line drawn at one, two, and three standarddeviations (sigmas) away from the mean.

Zone C is 1 sigma away from the mean (green). Zone B is 2 sigma away from the mean (yellow). Zone A is 3 sigma away from the mean (red).

8. 8
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Graph the X-bar Control Chart, by graphing the subgroup means (x-axis) verses

measurements (y-axis).Your graph should look like something like this:

9. 9Evaluate the graph to see if the process is out-of-control.The graph is out-of-control if

any of the following are true:

Any point falls beyond the red zone (above or below the 3-sigma line). 8 consecutive points fall on one side of the centerline. 2 of 3 consecutive points fall within zone A. 4 of 5 consecutive points fall within zone A and/or zone B. 15 consecutive points are within Zone C. 8 consecutive points not in zone C.
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10.10State whether the system is in-control or out-of-control.

EditSample Control Charts

Sample Control Chart

Sample Control Chart for Subgroups
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Sample Control Chart for Multiple Groups

EditVideo

EditTips

Excel commands that will make your data analyze easier are: Use Excel when creating your charts, because it has built in functions

(shown below) that will speed up your calculations.

EditWarnings

Control charts are (generally) based on data being normally distributed. Inpractice, however, they are reasonably robust to non-normal data.

For some charts, e.g. the c chart, data probably will be non-normallydistributed.

Moving Range charts (often used with the Individuals Chart (also knownas the X or I chart) use different interpretation rules to cater for the very

strong non-normality of Moving Range data.
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X-bar charts, such as the one explained above, chart means rather thanindividual values. As explained by the Central Limit Theorem, Means

tend to be normally distributed even if the underlying data are not.

How to Create a Control Chart

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