## Control Charts

Control charts measure the results of processes over time and display the results in graph form. Control charts are a way to measure variances to determine whether process variances are in control or out of control.

A control chart is based on sample variance measurements. From the samples chosen and measured, the mean and standard deviation are determined. Perform Quality Control is usually maintained—or said to be in control—within plus or minus three standard deviations. In other words, Perform Quality Control says that if the process is in control (that is, the measurements fall within the control limits), you know that 99.73 percent of the parts going through the process will fall within an acceptable range of the mean. If you discover a part outside of this range, you should investigate and determine whether corrective action is needed.

Figure 11.2 illustrates an example control chart.

FIGURE 11.2 Control chart

5.06

5.00

4.94

Upper

Control

Limit

Lower

Control

Limit

Let's assume you've determined from your sample measurements that 5 mm is the mean in the example control chart. One standard deviation equals 0.02. Three standard deviations on either side of the mean become your upper and lower control points on this chart. Therefore, if all control points fall within plus or minus three standard deviations on either side of the mean, the process is in control. If points fall outside the acceptable limits, the process is not in control and corrective action is needed.

Control charts are used most often in manufacturing settings where repetitive activities are easily monitored. For example, the process that produces widgets by the case lot must meet certain specifications and fall within certain variances to be considered in control. However, you aren't limited to using control charts only in the manufacturing industry. You can use them to monitor any output. You might consider using control charts to track and monitor project management processes. You could plot cost variances, schedule variances, frequency or number of scope changes, and so on to help monitor variances.

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