by Matthew Barsalou, guest blogger

Process capability analysis using Minitab Statistical Software’s Capability SixpackTM can be taught using a catapult. A process capability analysis is performed to determine if a process is statistically capable.

In my last blog post, I collected data from a first run of catapult results and found that the run not only had a large amount of variability, it also violated the assumption of normality. Now it's time to do a second run.  

The Second Run and Capability Analysis

A second run was performed using thicker and more robust wire to stretch the rubber band;...

by Matthew Barsalou, guest blogger

We can use a simple catapult to teach process capability analysis using Minitab Statistical Software’s Capability SixpackTM. Here's how.

A process capability analysis is performed to determine if a process is statistically capable. Based on the results of the capability study, we can estimate the amount of defective components the process would produce.

However, a process must be in statistical control and have a normal distribution. A process that is not in statistical control must be brought in control before the capability analysis is performed. In addition,...

by Cory Heid, guest blogger

Almost all of us have tried a Tootsie Pop at some point. I’m willing to bet that most of us also thought, “I wonder how many licks it does take to get to the center of the Tootsie Pop?” If you haven’t wondered about this, here’s the classic commercial that may get you more curious:

Personally, I was not very satisfied with the owl's answer of “3,” so I decided to continue the little boy’s quest to find the number of licks required to reach the center of a Tootsie Pop.

Research

Looking around the ‘net, I found that other studies done by student researchers at various...

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 optimal catapult setting using DOE, which I'll do with Minitab Statistical Software. (If you'd like to follow along but don't already have it, please download the 30-day free trial of Minitab.) 

Planning...

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 a catapult with multiple adjustable factors—and not to lay siege to a castle—so I don’t mind the rough appearance of my catapult.

The frame consists of two pieces of 40 cm x 4 cm x 2 cm wood, two...

by Robb Richardson, guest blogger

One of the things that I love most about my job is that I get to help educate, coach, and develop others on topics such as continuous improvement and data analysis.

In that capacity, one of the most frequently seen challenges is that team members and managers want to react to every data point. Their intentions are noble – but doing so is almost always an unnecessary exercise since these variations are a normal part of how the process behaves.

I’ve used lots of different examples to illustrate this point, but few seemed to resonate deeply with them and get them...

by Matthew Barsalou, guest blogger

For want of a nail the shoe was lost,
For want of a shoe the horse was lost,
For want of a horse the rider was lost
For want of a rider the battle was lost
For want of a battle the kingdom was lost
And all for the want of a horseshoe nail. (Lowe, 1980, 50)

According to the old nursery rhyme, "For Want of a Nail," an entire kingdom was lost because of the lack of one nail for a horseshoe. The same could be said for the Galactic Empire in Star Wars. The Empire would not have fallen if the technicians who created the first Death Star had done a proper Failure Mode and...

by Matthew Barsalou, guest blogger

In Jim Frost’s article “How to Be a Ghost Hunter with a Statistical Mindset,” he correctly pointed out the difficulties in distinguishing small effects from natural variation. However, he did not mention the benefits of doing measurement system analysis (MSA) in both ghost hunting as depicted by his example and in the statistical study using Minitab.

In industrial settings, testing equipment is evaluated to determine if the device used to assess the factor being studied is taking accurate measurements. In other words, are you collecting data that you can...

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 to analyze the data to see what effect our three factors have on our attribute response! 

Initial Model and Interaction Plot of Attribute DOE Results

We’ll do this by choosing Stat > DOE > Factorial...

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 how we can use DOE to optimize an attribute response, using data from the manufacturing sector. We are looking at 3 factors with 2 levels each, which are coded as -1 and +1. The total number of...