Blog posts and articles about using data analysis and statistics in quality improvement initiatives in manufacturing.

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
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
Measurement systems analysis (MSA) is essential to the success of any data analysis. If you cannot rely on the tool you’re using to take measurements, then why bother collecting data to begin with? It would be like trying to lose weight while relying on a scale that doesn’t work. What’s the point in weighing yourself? Minitab Statistical Software offers many types of tools that you can use to... Continue Reading
In my last post we looked at different discrete distributions and how you can use them. This time, I’ll show you how to determine whether your data follow a specific discrete distribution. (Read here to see how to identify the distribution of your continuous data.) Before we start testing discrete distributions, we need to distinguish between two general cases. In some cases, it is more important... Continue Reading
Previously, I’ve written about how to use Minitab to identify the distribution of your continuous data. That blog post prompted several questions about how to use and identify discrete distributions. If you are a quality improvement analyst who works with counts of defects or pass/fail inspections, you may be particularly interested in these types of discrete distributions. In this blog, I’ll show... Continue Reading
Sharing how people and companies use Minitab software to improve quality is without a doubt the highlight of my job! It never ceases to amaze me that a common thread among many organizations is the desire to keep continuous improvement at the forefront of their business. It’s also pretty neat that many of these same organizations trust Minitab to analyze their data and organize their quality... 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
For years, I thought I had arranged things so I would never be bothered by statistics. I thought I didn't like statistics. But even though I didn't use statistics, I was reaping the benefits of data analysis in the form of more reliable and safer products. You are too. In fact, right now you certainly have items in your home that have been made better by the application of Minitab Statistical Softwa... Continue Reading
We recently got a question from one of our friends on Facebook about stepwise regression. I’m new to stepwise regression myself, and I turned to a Minitab training manual for a little help in trying to explain this analysis. I found an interesting example about identifying the major sources of energy usage at a manufacturing plant that I thought might be helpful to share. When Is Stepwise... Continue Reading
I recently had the opportunity to learn about how synthetic yarn manufacturer Unifi Manufacturing Inc. used Minitab to optimize its false-twist texturing process. Many of you probably have several connections to Unifi yarns that you just don’t know about! In fact, you've probably found yourself wearing clothing made with Unifi yarns, or sitting on a couch made of stain-resistant fabric that was... Continue Reading
Variation is everywhere. It’s in your daily commute to work, it’s in the amount of caffeine you drink every day, in the number of e-mails that arrive in your inbox, etc. Whether you’re monitoring something as ordinary as caffeine consumption or something more important like a multi-million dollar manufacturing process, you can use one simple tool to monitor variation and determine whether the... Continue Reading
The other day a colleague of mine mentioned a use for Minitab's Tally command that I didn't know about. I thought I would share it with you in the form of contrived anecdote. I hope you enjoy it. Bob works at a manufacturing plant. You may remember Bob as the guy who was obsessed with gnomes. Well, his work with gnomes was so exemplary that he was promoted to work in the Garden Tool Division. Bob... Continue Reading
Manufacturers need to make items that meet a customer’s standards, or they’ll soon be out of business. That’s why quality engineers devote a good deal of time to making sure that processes are able to meet those standards.  The first step is to make sure your process is stable. After all, you can’t predict the performance of an unstable process. But you can predict and improve on a stable process.  I... Continue Reading
Everyone loves the soft feel of a cotton t-shirt! Unfortunately, the very properties that make cotton fabric so soft also make it prone to wrinkling and tearing. Researchers from the National Textile University in Faisalabad, Pakistan embarked on a study to predict the best fabric properties for strong, crease-free cotton—and they used Minitab to help. Cloth manufacturing plants strive to create a... Continue Reading
Today we announced the winner of the Minitab Experiment ContestFord, Bobcat, Smith & Nephew, Metalor, and more than a dozen other companies from many different industries entered the contest, which focused on using a statistical technique called Design of Experiments (DOE) to solve business problems.Quality improvement professionals use DOE to create experiments that provide insight into how... Continue Reading