Tips and Techniques for Statistics and Quality Improvement

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

Last week we began an experimental design trying to get at how to drive the golf ball the farthest off the tee by characterizing the process and defining the problem. The next step in our DOE problem-solving methodology is to design the data collection plan we’ll use to study the factors in the experiment.

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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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I had the pleasure of hosting the first of our Minitab Need to Knows webinars, Managing Your Data in Minitab, last week with our special guest Quentin Brook. We received several great questions throughout the hour. There are some we were not able to answer, so I followed up with Quentin and the team at Minitab for their answers. Here they are ... 

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As the vice president of quality for a $1.5 billion-dollar industrial corporation, Hermann Miskelly is responsible for leading its continuous improvement effort. Now in his 10th year of a Lean Six Sigma deployment, he has overseen the execution of more than 4,000 major improvement projects and another 6,000 small improvement projects. Here are three key insights he shared about managing continuous improvement...

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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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The role of quality professionals is more critical today than it ever has been. Quality is a top driver at any company, regardless of size or industry. It’s a major factor when it comes to production numbers, profits and more. However, maintaining and improving quality is no easy task.

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If you have a process that isn’t meeting specifications, using the Monte Carlo simulation and optimization tools in Companion by Minitab can help. Here’s how you, as an engineer in the medical device industry, could use Companion to improve a packaging process and help ensure patient safety. You can also check out our webinar recording, Seeing the Unknown: Identifying Risk and Quantifying Probability with Monte Carlo...

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Whatever stage you're at now with your Continuous Improvement initiatives, there was a lot to learn this month at Process Excellence (PEX) Europe Spring 2018, where practitioners and CI leaders met to "share and challenge everything you need to be a business of the future." We picked up three key CI lessons which we want to share with you in order to replicate success.

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Minitab’s R&D department uses modern design principles, including a user-centered design approach – adopting the Neilsen Norman Group’s (NN/g) methods and processes. NN/g is the world’s leader in all things usability. Hoa Loranger, their vice president, summarized their philosophy best: “UX without users Isn't UX.”

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If you collect and analyze real data for a living, the idea of using simulated data for a Monte Carlo simulation sounds a bit odd. How can you improve a real product with simulated data? 

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