Tips and Techniques for Statistics and Quality Improvement

Blog posts and articles about using Minitab software in quality improvement projects, research, and more.

Control charts take data about your process and plot it so you can distinguish between common-cause and special-cause variation. Knowing the difference is important because it permits you to address potential problems without over-controlling your process.  

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All processes have variation, some of which is inherent in the process, and isn't a reason for concern. But when processes show unusual variation, it may indicate a change or a "special cause" that requires your attention. 

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Control charts are excellent tools for looking at data points that seem unusual and for deciding whether they're worthy of investigation. If you use control charts frequently, then you're used to the idea that if certain subgroups reflect temporary abnormalities, you can leave them out when you calculate your center line and control limits. If you include points that you already know are different because of an...

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Rare events inherently occur in all kinds of processes. In hospitals, there are medication errors, infections, patient falls, ventilator-associated pneumonias, and other rare, adverse events that cause prolonged hospital stays and increase healthcare costs. 

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Users often contact Minitab technical support to ask how the software calculates the control limits on control charts.

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As a member of Minitab's Technical Support team, I get the opportunity to work with many people creating control charts. They know the importance of monitoring their processes with control charts, but many don’t realize that they themselves could play a vital role in improving the effectiveness of the control charts.  

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by Kevin Clay, guest blogger

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In its industry guidance to companies that manufacture drugs and biological products for people and animals, the Food and Drug Administration (FDA) recommends three stages for process validation: Process Design, Process Qualification, and Continued Process Verification. In this post, we we will focus on that third stage.

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A recent discussion on the Minitab Network on LinkedIn pertained to the I-MR chart. In the course of the conversation, a couple of people referred to it as "The Swiss Army Knife of control charts," and that's a pretty great description. You might be able to find more specific tools for specific applications, but in many cases, the I-MR chart gets the job done quite adequately.

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Have you ever wished your control charts were better?  More effective and user-friendly?  Easier to understand and act on?  In this post, I'll share some simple ways to make SPC monitoring more effective in Minitab.

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