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This third article introduces the Control Chart, also known as Shewart Chart, a graph used to study how a process changes over time. The data is plotted in time order with a central line showing the average, an upper line for the upper control limit, and a lower line for the lower control limit all determined from historical data. By comparing the current data to the historical lines, conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation) can be drawn.

This series of articles presents the 7 Basic Quality Tools for Process Improvement used in the field. These are defined as instruments or techniques to support and improve the activities of quality management and improvement. ASQ has made available to the members and the public a huge amount of information on the "quality" body of knowledge (BOK). It is only meant to be a starting point, but oh so useful.

When to Use a Control Chart:

• When controlling ongoing processes by finding and correcting problems as they occur;
• When predicting the expected range of outcomes from a process;
• When determining whether a process is stable (in statistical control);
• When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process);
• When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.

Control Chart Procedure: Read the full article on preparing a control charts. Basically, you collect consecutive data points from a process on a control chart worksheet (Excel). You can then calculate the appropriate control chart parameters and determine the proper time period for further collecting and plotting of data. Once that is done, you collect more data, construct your chart and analyze it (see below). You can the "read" the chart to look for "out-of-control signals". When one is identified, you mark it on the chart and investigate the cause — document how you investigated, what you learned, the cause and how it was corrected.

§ This News post was adapted by J.P. Amiel, ASQ Senior, CQA ret., Web committee Chair, from content at ASQ's Quality Resources pages, which are excerpted and adapted from The Quality Toolbox, Second Edition, ASQ Quality Press.

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History: The control chart was invented by Walter A. Shewhart, one of the founders of the quality approach, while working for Bell Labs in the 1920s. The company's engineers had been seeking to improve the reliability of their telephony transmission systems and had already realized the importance of reducing variation in a manufacturing process. Shewhart framed the problem in terms of Common- and special-causes of variation. On May 16, 1924, he wrote a one page internal memo introducing the control chart as a tool for distinguishing between the two. He stressed that bringing a production process into a state of statistical control, where there is only common-cause variation, and keeping it in control, is necessary to predict future output and to manage a process economically. This created the basis for the control chart and the concept of a state of statistical control by carefully designed experiments. While Shewhart drew from pure mathematical statistical theories, he understood that data from physical processes typically produce a "normal distribution curve" (a Gaussian distribution, commonly referred to as a "bell curve"). He concluded that while every process displays variation, some processes display controlled variation that is natural to the process, while others display uncontrolled variation that is not present in the process causal system at all times. (Wikipedia)

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