Tips and Techniques for Statistics and Quality Improvement

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

Bruno Scibilia

I practiced quality improvement statistical techniques in manufacturing for many years, and I look forward to sharing some of what I've learned about quality improvement with you!
Bruno Scibilia

There are many reasons why a distribution might not be normal/Gaussian. A non-normal pattern might be caused by several distributions being mixed together, or by a drift in time, or by one or several outliers, or by an asymmetrical behavior, some out-of-control points, etc.

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Having delivered training courses on capability analyses with Minitab, several times, I have noticed that one question you can be absolutely sure will be asked, during the course, is: What is the difference between the Cpk and the Ppk indices?

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When performing a design of experiments (DOE), some factor levels may be very difficult to change—for example, temperature changes for a furnace. Under these circumstances, completely randomizing the order in which tests are run becomes almost impossible.To minimize the number of factor level changes for a Hard-to-Change (HTC) factor, a split-plot design is required.

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Kappa statistics are commonly used to indicate the degree of agreement of nominal assessments made by multiple appraisers. They are typically used for visual inspection to identify defects. Another example might be inspectors rating defects on TV sets: Do they consistently agree on their classifications of scratches, low picture quality, poor sound?  Another application could be patients examined by different doctors...

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The Cp and Cpk are well known capability indices commonly used to ensure that a process spread is as small as possible compared to the tolerance interval (Cp), or that it stays well within specifications (Cpk).

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Imagine that you are watching a race and that you are located close to the finish line. When the first and fastest runners complete the race, the differences in times between them will probably be quite small.

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Suppose that you have designed a brand new product with many improved features that well help create a much better customer experience. Now you must ensure that it is manufactured according to the best quality and reliability standards, so that it gets the excellent long-term reputation it deserves from potential customers. You need to move quickly and seamlessly from Research and Development into mass production. To...

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In my recent meetings with people from various companies in the service industries, I realized that one of the problems they face is that they were collecting large amounts of "qualitative" data: types of product, customer profiles, different subsidiaries, several customer requirements, etc.

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In several previous blogs, I have discussed the use of statistics for quality improvement in the service sector. Understandably, services account for a very large part of the economy. Lately, when meeting with several people from financial companies, I realized that one of the problems they faced was that they were collecting large amounts of "qualitative" data: types of product, customer profiles, different...

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Using statistical techniques to optimize manufacturing processes is quite common now, but using the same approach on social topics is still an innovative approach. For example, if our objective is to improve student academic performances, should we increase teachers wages or would it be better to reduce the number of students in a class?

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