Tips and Techniques for Statistics and Quality Improvement

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

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Performing DOE for Defect Reduction

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... read more »

Analyze a DOE with the Assistant in Minitab

The Assistant in Minitab Statistical Software includes Design of Experiments (DOE). We already spent some time looking at 5 highlights when you create a screening experiment with the Assistant in Minitab. 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 and Interpret and you’re... read more »

DOE—It's Not Just for Widgets Anymore

When you think of design of experiments (DOE), what types of applications come to mind? Do visions of camshafts, widgets, capacitors, resistors, and other industrial thingamabobs dance in your head?   If so, that's probably because DOE has such powerful and successful applications in manufacturing. Those experiments often involve changing levels of physical factors, such as temperature or pressure... read more »

Leveraging Designed Experiments (DOE) for Success

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... read more »

A DOE in a Manufacturing Environment (Part 2)

In my last post, I discussed how a DOE was chosen to optimize a chemical-mechanical polishing process in the microelectronics industry. This important process improved the plant's final manufacturing yields. We selected an experimental design that let us study the effects of six process parameters in 16 runs. Analyzing the Design Now we'll examine the analysis of the DOE results after the actual... read more »

A DOE in a Manufacturing Environment (Part 1)

I used to work in the manufacturing industry. Some processes were so complex that even a very experienced and competent engineer would not necessarily know how to identify the best settings for the manufacturing equipment. You could make a guess using a general idea of what should be done regarding the optimal settings, but that was not sufficient. You need very precise indications of the correct... read more »

Gummi Bear DOE: Mystery Effects

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... read more »

Gummi Bear DOE: Choosing a Design

Now that we’ve learned enough about design of experiments to understand the experimental designs that Minitab offers, it’s time  to consider which we should use to study the gummi bears. We'll consider the designs in the same order that we did in the earlier blog posts: General full factorial designs Split-plot designs Plackett-Burman designs What Type of Design do I Need? Here's a series of... read more »

Design of Experiments: "Fractionating" and "Folding" a DOE

Design of experiments (DOEs) is a very effective and powerful statistical tool that can help you understand and improve your processes, and design better products. DOE lets you assess the main effects of a process as well as the interaction effects (the effect of factor A, for example, may be much larger when factor B is set at a specific level, leading to an interaction). In science and... read more »

Gummi Bear DOE: The Importance of Randomization

If you pay close attention to this series on using gummi bears to understand design of experiments, you noticed that in my last post I mentioned pressure as a variable for the first time. Pressure wasn’t on the fishbone diagram that I used when planning variables, even though it’s just as obvious as temperature and humidity. I’ve been referring to the fishbone diagram quite a bit, but I... read more »

Applying DOE for Great Grilling, part 1

Design of Experiments (DOE) has a reputation for difficulty, and to an extent, this statistical method deserves that reputation. While it's easy to grasp the basic idea—acquire the maximum amount of information from the fewest number of experimental runs—practical application of this tool can quickly become very confusing.  Even if you're a long-time user of designed experiments, it's still easy... read more »

Gummi Bear DOE: Choosing Factor Levels

Now that we've explored all of the DOE design choices in Minitab Statistical Software, it's time to think about the levels of the factors. I chose these 5 factors previously: Position of catapult on the launch ramp Angle of catapult Number of rubber band windings Position of gummi bear on the catapult Position of fulcrum in the catapult What Is an Effect in DOE? In DOE, we're trying to detect the... read more »

Create a DOE Screening Experiment with the Assistant in Minitab 17

For me, the biggest enhancement in Minitab 17 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 chance to study DOE with an expert. If not, even the flow... read more »

Using Designed Experiments (DOE) to Minimize Moisture Loss

As a person who loves baking (and eating) cakes, I find it bothersome to go through all the effort of baking a cake when the end result is too dry for my taste. For that reason, I decided to use a designed experiment in Minitab to help me reduce the moisture loss in baked chocolate cakes, and find the optimal settings of my input factors to produce a moist baked chocolate cake. I’ll share the... read more »

Applying DOE for Great Grilling, part 2

Design of Experiments is an extremely powerful statistical method, and we added a DOE tool to the Assistant in Minitab to make it more accessible to more people. Since it's summer grilling season, I'm applying the Assistant's DOE tool to outdoor cooking. Earlier, I showed you how to set up a designed experiment that will let you optimize how you grill steaks.  If you're not already using it and... read more »

8 Expert Tips for Excellent Designed Experiments (DOE)

If your work involves quality improvement, you've at least heard of Design of Experiments (DOE). You probably know it's the most efficient way to optimize and improve your process. But many of us find DOE intimidating, especially if it's not a tool we use often. How do you select an appropriate design, and ensure you've got the right number of factors and levels? And after you've gathered... read more »

Holiday Baking: Using DOE to Bake a Better Cookie

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 quality... read more »

Wave a Magic Wand Over Your DOE Analyses

As a member of Minitab's Technical Support team, I get the opportunity to work with many people using DOE (Design of Experiments). People often will call after they've already chosen their design, run the experiment, and identified the important factors in their process. But now what? They have to find the best settings, but with several factors and responses, what should they do? "I wish I had a... read more »

Doggy DOE Part II: Create Your Design

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... read more »

Getting Started with Factorial Design of Experiments (DOE)

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,... read more »