# 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!

This is an era of massive data. A huge amount of data is being generated from the web and from customer relations records, not to mention also from sensors used in the manufacturing industry (semiconductor, pharmaceutical, petrochemical companies and many other industries).

In my last post, I discussed how a DOE was chosen to optimize a chemical-mechanical polishing process in the microelectronics industry. This important process improved the plant's final manufacturing yields. We selected an experimental design that let us study the effects of six process parameters in 16 runs.

## I used to work in the manufacturing industry. Some processes were so complex that even a very experienced and competent engineer would not necessarily know how to identify the best settings for the manufacturing equipment.

You could make a guess using a general idea of what should be done regarding the optimal settings, but that was not sufficient. You need very precise indications of the correct process parameters,...

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.

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?

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.

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...