Tips and Techniques for Statistics and Quality Improvement

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

Confidence intervals show the range of values we can be fairly, well, confident, that our true value lies in, and they are very important to any quality practitioner. I could be 95% confident the volume of a can of soup will be 390-410 ml. I could be 99% confident under 2% of the products in my batch are defective.

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Stability is a major issue in manufacturing. Parts need to be made to specifications to allow an easy assembly of final products. Unstable behaviors generate quality problems that customers must deal with later.

Yet there are often so many consecutive steps that a slight misalignment at one will impact the entire production line. Read on to see four challenges to stability, and how to address them.

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Great stories others want to hear. Common challenges we have all faced before (or might even be facing right now). Discovering new tools in Minitab software as shared by peers. Engaging walkthroughs of finding insights in your data, and recommendations on how to act on them. All packed into a few days of learning and fun.

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Definitive Screening Designs (DSDs) are a new class of Designs of Experiments (DoE) that have generated a lot of interest for product and process optimization. They are available in Minitab Statistical Software.

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Process validation is vital to the success of companies that manufacture pharmaceutical drugs, vaccines, test kits and a variety of other biological products for people and animals. According to FDA guidelines, process validation is “the collection and evaluation of data, from the process design state through commercial production, which establishes scientific evidence that a process is capable of consistently...

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You might be thinking, six weeks and you’re still not telling us what happened? When you are solving a manufacturing or development problem you might hear the same thing from your leadership – when will we get the results?

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The potential benefit of the data stored on servers is huge. Banks, insurance companies, telecom companies, manufacturers — in fact organizations from across all industries need to make good use of the data they own to improve their operations, better understand their customers and find competitive advantage.

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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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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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Tomorrow marks the 47th anniversary of the premiere of the great 1971 movie Willy Wonka and the Chocolate Factory, wherein the reclusive owner of the Wonka Chocolate Factory decides to place golden tickets in five of his famous chocolate bars, and allow the winners of each to visit his factory with a guest. Since restarting production after three years of silence, no one has come in or gone out of the factory....

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