Tips and Techniques for Statistics and Quality Improvement

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

Minitab Blog Editor

Minitab Blog Editor

Value stream mapping is a cornerstone of the Lean process improvement methodology, and also is a recognized tool used in Six Sigma. A value stream map illustrates the flow of materials and information as a product or service moves through a process. Creating a “current state” value stream map can help you identify waste and also makes it easier to envision an improved state for process in the future.

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The abbreviation FMEA is short for Failure Modes and Effects Analysis. It's a tool that helps you look very carefully and systematically at exactly how and why things can go wrong, so you can do your best to prevent that from happening.

 

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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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Choosing the correct linear regression model can be difficult. Trying to model it with only a sample doesn’t make it any easier. In this post, we'll review some common statistical methods for selecting models, complications you may face, and provide some practical advice for choosing the best regression model.

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Healthcare has many data-rich opportunities which can be used to improve cycle times, customer satisfaction scores, wait times, capacity/throughput, and inventory. In honor of Healthcare Quality Week October 21-27, 2018, National Quality Month in the US in October and World Quality Month in November, we wanted to share this helpful how-to on value stream mapping, or VSM. Value stream mapping can help you map,...

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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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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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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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