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Design of Experiments

How to apply the statistical method called Design of Experiments (DOE) for quality improvement and research.

Design of experiments (DOE) is an extremely practical and cost-effective way to study the effects of different factors and their interactions on a response. But finding your way through DOE-land can be daunting when you're just getting started. So I've enlisted the support of a friendly golden retriever as a guide dog to walk us through a simple DOE screening experiment. Nala, the golden retriever,... Continue Reading
Recently, a customer called our Technical Support team about a Design of Experiment he was performing in Minitab Statistical Software. After they helped to answer his question, the researcher pointed our team to an interesting DOE he and his colleagues conducted that involved using nasal casts to predict the drug delivery of nasal spray. The study has already been published, and you can read... Continue Reading
All processes are affected by various sources of variations over time. Products which are designed based on optimal settings, will, in reality, tend to drift away from their ideal settings during the manufacturing process. Environmental fluctuations and process variability often cause major quality problems. Focusing only on costs and performances is not enough. Sensitivity to deterioration and... Continue Reading
The 2013 ASQ World Conference is taking place this week in Indianapolis, Indiana, and it's been a treat to see how our software was used in the projects highlighted in many of the presentations. As a supporter of the conference, a key event for quality practitioners around the world, Minitab was proud to sponsor one of the presentations that seemed to get a lot of attendees talking. Scott... Continue Reading
You know the drill…you’re in Six Sigma training and you’re learning how to conduct a design of experiment (DOE). Everything is making sense, and you’ve started thinking about how you’ll apply what you are learning to find the optimal settings of a machine on the factory floor. You’ve even got the DOE setup chosen and you know the factors you want to test … Then … BAM! … You’re on your own and you... Continue Reading
When I talk to quality professionals about how they use statistics, one tool they mention again and again is design of experiments, or DOE. I'd never even heard the term before I started getting involved in quality improvement efforts, but now that I've learned how it works, I wonder why I didn't learn about it sooner. If you need to find out how several factors are affecting a process outcome,... Continue Reading
by Matthew Barsalou, guest blogger In my last post, I shared my plans for building a simple do-it-yourself catapult for performing experiments to practice using design of experiments (DOE).  That's the completed catapult there on the right. If you want to build your own, here are my plans and instructions in a PDF.   Now that my catapult is built, I have one last step to complete:  to find the... Continue Reading
by Matthew Barsalou, guest blogger I needed to find a way to perform experiments to practice using design of experiments (DOE), so I built a simple do-it-yourself (DIY) catapult. The basic plan for the catapult is based on the table-top troll catapult from http://www.stormthecastle.com/catapult/how-to-build-a-catapult.htm. My catapult is not as attractive as the troll catapult; my goal was to build... Continue Reading
Lean Six Sigma and process excellence leaders are often asked to “remove defects” from products and processes. This can be quite a challenge! Lou Johnson, senior Minitab technical trainer and mentor, has some tips that might help if you’re faced with this situation. I had the chance to talk with Lou, and here’s what he shared with me about how to first approach a DOE. How to Approach a DOE Before... Continue Reading
It’s the most wonderful time of the year – the time for holiday bakers and cookie monsters to unite! So what’s a quality improvement professional to do when his favorite sugar cookie recipe produced cookies that failed to hold their festive holiday shapes after being baked? Run a Design of Experiment (DOE), of course! A Fractional Factorial Experiment Bill Howell, an avid baker and... Continue Reading
Design of experiments, experimental design, or just "gathering some data." Whatever you want to call it, your approach to doing it will affect the results you get. Have you ever wondered about all those contradictory studies in the news, especially regarding what's good and bad for you? Coffee is good for you, one headline says. It's bad for you, says the next. And if you read beyond the headlines,... Continue Reading
We’ve used design of experiments to look at the data. We’ve seen that the center points are statistically insignificant. We’ve seen that blocks help account for the unstable conditions during the collection of the data. Now for the exciting part: let’s choose a model to use to predict where the gummi bears will land when we launch them. Various criteria exist for how to choose a model, so we’re... Continue Reading
Last time I used design of experiments to look at the gummi bear data, I interpreted the center point data. The data say that I won’t need any square or cubic terms to get a good fit to the data. Traditionally, the next effect to look at in design of experiments is the block effect. I was worried that there would be a wearout effect acting on my catapult, so I changed popsicle sticks and rubber... Continue Reading
When I chose a full factorial design for my gummi bear experiment, I was using traditional design of experiments practice to try to learn the most from the least amount of data. I wanted to see if I could save myself the 10 or more data points I would need to add to the design to estimate nonlinear effects. Now that I have some data, the first thing I’m going to learn is: Do I need to collect... Continue Reading
Back when I chose the factors to study for my gummi bear design of experiments, I was thinking about the fact that something like the position of the gummi bear and the position of the fulcrum would probably interact. When I finished collecting the data, I was eager to see if that effect showed up in my analysis. Before we look at the distance parallel to the catapult, let's look at the distance... Continue Reading
I collected my first block of data for the gummi bear design of experiments this week. Why not all of it? Well, there’s lots you can learn when you start collecting data for real. Here are some of my thoughts: Enter data quickly and accurately for design of experiments If you’re going to do anything with your data, it’s a lot easier to have it in Minitab. If you followed my lead for doing design... Continue Reading
The Minitab Fan section of the Minitab blog is your chance to share with our readers! We always love to hear how you are using Minitab products for quality improvement projects, Lean Six Sigma initiatives, research and data analysis, and more. Today we learn how an avid gamer used design of experiments to boost his performance in his favorite driving game. If our software has helped you, please sha... Continue Reading
by Manikandan Jayakumar, guest blogger In an earlier post, I discussed how to collect data in a Design of Experiments (DOE) to optimize the value of an attribute or categorical response (Pass/Fail, Accept/Reject, etc.).  I then showed how to convert the collected data into proportions and apply the arcsine transformation using built-in calculator in Minitab Statistical Software.    Now we’re ready... Continue Reading
Recently, we’ve discussed how to do the design and factor setup for design of experiments in Minitab Statistical Software. We’re almost ready to launch some gummi bears. But there’s something else to consider. When we produce the data for design of experiments, how does the data get from the measuring device to Minitab? If you’re lucky, you have an electronic thingamajig that takes measurements... Continue Reading
by Manikandan Jayakumar, guest blogger We use Design of Experiments (DOE) to optimize the value of a response (Y) by simultaneously changing the values of several factors (X’s). The response will often be a continuous variable, but in some scenarios you need to optimize an attribute or categorical response (Pass/Fail, Accept/Reject, etc.).  Collecting the Data for an Attribute Response DOE Let’s see... Continue Reading