Tips and Techniques for Statistics and Quality Improvement

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

 

Previously in our designed experiment on driving the golf ball as far as possible from the tee, we tested our four experimental factors and determined how many runs we needed to produce a complete data set.

Now let’s analyze the data and interpret the covariates and blocking variables.

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Rafael Villa is a chemical engineer working as a Research and Development leader in the home care division of a company in Peru. His company that manufactures a vast range of consumer package goods and B2B products ranging from food items, such as cereal and candies, to cleaning supplies and home good items. Focusing on the design, formulation and optimization of consumer products, his R&D career has spanned multiple...

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In our continuing effort to use experimental design to understand how to drive the golf ball the farthest off the tee, we have decided each golfer will perform half the possible combinations of high and low settings for each factor. But how many times should each golfer replicate their runs to produce a complete data set?

 

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Editor’s note: As we prepare for the inaugural Minitab Insights golf tournament in Scottsdale, Arizona on September 12, we are taking a look back at The Minitab Blog archives with some posts on using Minitab to understand how to improve our game. In this first installment, we examine how solving an age-old problem in golf is much like process engineering problems. Stay tuned each week as we cover the next step in our...

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Do you have an insurance policy that will pay out if your car gets damaged? Do you pay the premium because you know your car will be damaged? No, you pay it so that if you do damage your car you will get a payment to cover the damage.

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As a person who loves baking (and eating) cakes, I find it bothersome to go through all the effort of baking a cake when the end result is too dry for my taste. For that reason, I decided to use a designed experiment in Minitab to help me reduce the moisture loss in baked chocolate cakes, and find the optimal settings of my input factors to produce a moist baked chocolate cake. I’ll share the details of the design and...

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Genichi Taguchi is famous for his pioneering methods of robust quality engineering. One of the major contributions that he made to quality improvement methods is Taguchi designs.

Designed experiments were first used by agronomists during the last century. This method seemed highly theoretical at first, and was initially restricted to agronomy. Taguchi made the designed experiment approach more accessible to...

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Process validation is vital to the success of companies that manufacture drugs and biological products for people and animals. According to the FDA guidelines published by the U.S. Department of Health and Human Services:

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If your work involves quality improvement, you've at least heard of Design of Experiments (DOE). You probably know it's the most efficient way to optimize and improve your process. But many of us find DOE intimidating, especially if it's not a tool we use often. How do you select an appropriate design, and ensure you've got the right number of factors and levels? And after you've gathered your data, how do you pick...

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You’ve performed multiple linear regression and have settled on a model which contains several predictor variables that are statistically significant. At this point, it’s common to ask, “Which variable is most important?”

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