Design of Experiments

Blog posts and articles about the the statistical method called Design of Experiments in quality improvement.

NOTE: This story will reveal how easy it can be to optimize settings using the statistical method called Design of Experiments, but it won't provide easy answers for making your own office coffee any better. After her team’s ultimatum about the wretched office coffee, Jill used the design-of-experiments (DOE) tool in Minitab 17’s Assistant to design and analyze a screening study. Jill now knew... Continue Reading
NOTE: This story reveals how easy it can be to identify important factors using the statistical method called Design of Experiments. It won't provide easy answers for making your own office's coffee any better, but it will show you how you can begin identifying the critical factors that contribute to its quality. At their weekly meeting, her team gave Jill an ultimatum: Make the coffee better. The... Continue Reading
by Iván Alfonso, guest blogger I'm a huge fan of hot cakes—they are my favorite dessert ever. I’ve been cooking them for over 15 years, and over that time I’ve noticed many variation in textures, flavor, and thickness. Personally, I like fluffy pancakes. There are many brands of hotcake mix on the market, all with very similar formulations. So I decided to investigate which ingredients and inputs... Continue Reading
There is more than just the p value in a probability plot—the overall graphical pattern also provides a great deal of useful information. Probability plots are a powerful tool to better understand your data. In this post, I intend to present the main principles of probability plots and focus on their visual interpretation using some real data. In probability plots, the data density distribution... Continue Reading
There is high pressure to find low P values. Obtaining a low P value for a hypothesis test is make or break because it can lead to funding, articles, and prestige. Statistical significance is everything! My two previous posts looked at several issues related to P values: P values have a higher than expected false positive rate. The same P value from different studies can correspond to different false... Continue Reading
Minitab Statistical Software was born out of a desire to make statistics easier to learn: by making the calculations faster and easier with computers, the trio of educators who created the first version of Minitab sought to free students from intensive computations to focus on learning key statistical concepts. That approach resonated with statistics instructors, and today Minitab is the standard... Continue Reading
It’s common to think that process improvement initiatives are meant to cater only to manufacturing processes, simply because manufacturing is where Lean and Six Sigma began. However, many other industries, in particular financial services and banking, also rely on data analysis and Lean Six Sigma tools to improve processes. Rod Toro is a business process improvement manager at Edward Jones, and I... Continue Reading
The 2014 ASQ World Conference on Quality and Improvement is coming up in early May in Dallas, and this year’s International Team Excellence Award Process (ITEA) will also come to a close at the conference, as winners from the finalist teams will be chosen for ASQ gold, silver, or bronze-level statuses. What’s ITEA? The annual ASQ ITEA process celebrates the accomplishments of quality improvement... Continue Reading
By now, you probably know that Minitab 17 includes Design of Experiments (DOE) in the Assistant. We already spent some time looking at 5 highlights when you create a screening experiment with the Assistant in Minitab 17. But the Assistant can also help you make sense of the data you collect for your experiment. After you create a design with the Assistant, choose Assistant > DOE > Analyze... Continue Reading
If you’ve been looking at Minitab 17, you’ve noticed a lot of new enhancements. For me, the biggest of these is the addition of Design of Experiments (DOE) to the Assistant. DOE in the Assistant has so many exciting aspects it’s hard to take it all in at once, but here are 5 highlights for when you plan and create a screening experiment: 1. Just-in-time guidance If you’re lucky, you’ve had the... Continue Reading
By popular demand, Release 17 of Minitab Statistical Software comes with a new graphical analysis called the Bubble Plot. This exploratory tool is great for visualizing the relationships among three variables on a single plot. To see how it works, consider the total medal count by country from the recently completed 2014 Olympic Winter Games. Suppose I want to explore whether there might be a... Continue Reading
In Parts 1 and 2 of Gauging Gage we looked at the numbers of parts, operators, and replicates used in a Gage R&R Study and how accurately we could estimate %Contribution based on the choice for each.  In doing so, I hoped to provide you with valuable and interesting information, but mostly I hoped to make you like me.  I mean like me so much that if I told you that you were doing... Continue Reading
In Part 1 of Gauging Gage, I looked at how adequate a sampling of 10 parts is for a Gage R&R Study and providing some advice based on the results. Now I want to turn my attention to the other two factors in the standard Gage experiment: 3 operators and 2 replicates.  Specifically, what if instead of increasing the number of parts in the experiment (my previous post demonstrated you would need... Continue Reading
Minitab 17 came out yesterday and it’s got quite a few neat features in it. You can check some of them out on the What’s New in Minitab 17 page. But one of my very favorite things is related to one of my previous blog posts that showed how to make histograms that are easy to compare. Turns out, you don’t need those steps anymore. You can do it all with Minitab’s Assistant. Here’s how to open the... Continue Reading
In my previous post, I shared a case study of how a small bicycle-chain manufacturing company in India used the DMAIC approach to Six Sigma to reverse declining productivity. After completing the Define, Measure, and Analysis phases, the team had identified the important factors in the bushing creation process. Armed with this knowledge, they were now ready to make some improvements. The Improve... Continue Reading
I had the opportunity to speak with a great group of students from the New Jersey Governor’s School of Engineering and Technology—a summer program for high-achieving high school students. Students in the program complete a set of challenging courses while working in small groups on real-world research and design projects that relate to the field of engineering. Governor’s School students... Continue Reading
What factors significantly affect how quickly my couch-potato pooch obeys the “Lay Down” command? The cushiness of the floor surface? The tone of voice used? The type of reward she gets? How hungry she is? I created a 1/8 fraction Resolution IV design for 7 factors and collected response data for 16 runs. Now it’s time to analyze the data in Minitab, using  Stat > DOE > Factorial > Analyze Factorial... Continue Reading
Nala, our 6-year-old golden retriever, loves her dogma. That's her sitting in front of church on Sunday morning. But she's not crazy about her catechism. For example, she doesn't always dutifully follow the "Lay Down" commandment.   What factors may be influencing her response? We're performing a DOE screening experiment to find out. In this post, we'll use Minitab Statistical Software to Create the... Continue Reading
A colleague of mine at Minitab, Cheryl Pammer, was recently featured in "A Statistician's Journey," a monthly feature that appears in the print and online versions of the American Statistical Association's AMSTAT News magazine.   Each month, the magazine asks ASA members to talk about the paths they took to get to where they are today. Cheryl is a "user experience designer" at Minitab. In other... Continue Reading