Tips and Techniques for Statistics and Quality Improvement

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

The other day I was talking with a friend about control charts, and I wanted to share an example one of my colleagues wrote on the Minitab Blog.  Looking back through the index for "control charts" reminded me just how much material we've published on this topic.

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To assess if a process is stable and in statistical control, you can use a control chart. It lets you answer the question "is the process that you see today going to be similar to the process that you see tomorrow?" To assess and quantify how well your process falls within specification limits, you can use capability analysis.

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by Matthew Barsalou, guest blogger

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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).

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Control charts are a fantastic tool. These charts plot your process data to identify common cause and special cause variation. By identifying the different causes of variation, you can take action on your process without over-controlling it.

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Hi everyone! Over the past month, I fielded some interesting customer calls regarding control chart creation and editing. I wanted to share these potential scenarios with you in hopes that you will find them informative and useful. For these scenarios, I used the XBar-R chart as my template, but you could easily apply them to many of the other control charts in Minitab. 

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Keeping your vehicle fueled up is expensive. Maximizing the miles you get per gallon of fuel saves money and helps the environment, too. 

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by Lion "Ari" Ondiappan Arivazhagan, guest blogger

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Minitab’s Assistant got a lot of splashy upgrades for Minitab 17. The addition of DOE and multiple regression to the Assistant are large feature improvements with obvious advantages. But there are many subtler, but still fantastic additions that shouldn't be overlooked.

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When it comes to creating control charts, it's generally good to collect data in subgroups, if possible. But sometimes gathering subgroups of measurements isn't an option. Measurements may be too expensive. Production volume may be too low. Products may have a long cycle time.

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