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Control Charts


Control Charts are used for monitoring, analyzing and predicting process performances and identifying alternatives for process improvement. Control charts are easy to understand and easy to use quality management tools and are excellent communication tool as well. Control charts show whether the process being measured is in control which means whether the process output is within predictable and controllable range of variation. In other words by using control charts we are tracking whether the process is statistically in control or statistically out of control. The use of control charts starts with measuring the process performances over time or collecting process data and calculating the control limits LCL (Lower Control Limit) and UCL (Upper Control Limit) and adding an average or mean value line to your control chart. Once you have calculated these three lines you can add these lines to your control chart. As you continuously gather data from your process you use your data in your control chart and track process performances over time.

There are different types of control charts depending on the type of process measurement and they are generally divided in two major categories:

1. Variable data control charts (X and mR, Xbar and R, and Xbar and S control charts)

2. Attribute data control charts (c chart, u chart, np chart, and p chart)

The type of control chart you need to use depends on the type of data you have and the sample size. Use this control chart reference to decide what type of control chart you need to use for your data:




In addition to data visualization control charts help us distinguish between special causes of variation and common causes of variation. Special causes of variation are large fluctuations in the data which are not inherent to a process (they represent potential problems or opportunities). Common causes of variation are inherent variability that exists in the system.


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