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

Whatever industry you're in, you're going to need to buy supplies. If you're a printer, you'll need to purchase inks, various types of printing equipment, and paper. If you're in manufacturing, you'll need to obtain parts that you don't make yourself.  But how do you know you're making the right choice when you have multiple suppliers vying to fulfill your orders?  How can you be sure you're... Continue Reading
by Erwin Gijzen, Guest Blogger People who work in quality improvement know that the root causes of quality issues are hard to find. A typical production process can contain hundreds of potential causes. Additionally, companies often produce products with multiple quality requirements, such as dimensions, surface appearance, and impact resistance. With so many variables, it’s no wonder many companies... Continue Reading


Smarter Process Improvement

with Companion by Minitab

This week I'm at the American Society for Quality's World Conference on Quality and Improvement in Nashville, TN. The ASQ conference is a great opportunity to see how quality professionals are tackling problems in every industry, from beverage distribution to banking services.  Given my statistical bent, I like to see how companies apply tools like ANOVA, regression, and especially... Continue Reading
A while back, I offered an overview of process capability analysis that emphasized the importance of matching your analysis to the distribution of your data. If you're already familiar with different types of distributions, Minitab makes it easy to identify what type of data you're working with, or to transform your data to approximate the normal distribution. But what if you're not so great with... Continue Reading
The Cp and Cpk are well known capability indices commonly used to ensure that a process spread is as small as possible compared to the tolerance interval (Cp), or that it stays well within specifications (Cpk). Yet another type of capability index exists: the Cpm, which is much less known and used less frequently. The main difference between the Cpm and the other capability indices is that the... Continue Reading
Suppose that you have designed a brand new product with many improved features that well help create a much better customer experience. Now you must ensure that it is manufactured according to the best quality and reliability standards, so that it gets the excellent long-term reputation it deserves from potential customers. You need to move quickly and seamlessly from Research and Development into... Continue Reading
In technical support, we frequently receive calls from Minitab users who have questions about the differences between Cpk and Ppk.  Michelle Paret already wrote a great post about the differences between Cpk and Ppk, but it also helps to have a better understanding of the math behind these numbers. So in this post I will show you how to calculate Ppk using Minitab’s default settings when the... Continue Reading
Suppose that you plan to source a substantial amount of parts or subcomponents from a new supplier. To ensure that their quality level is acceptable to you, you might want to assess the capability levels (Ppk and Cpk indices) of their manufacturing processes and check whether their critical process parameters are fully under control (using control charts). If you are not sure about the efficiency... Continue Reading
Keeping your vehicle fueled up is expensive. Maximizing the miles you get per gallon of fuel saves money and helps the environment, too.  But knowing if you're getting good mileage requires some data analysis, which gives us a good opportunity to apply one of the common tools used in Six Sigma -- the I-MR (individuals and moving range) control chart to daily life.    Finding Trends or Unusual... Continue Reading
Ughhh... your process is producing some parts that don't meet your customer's specifications! Fortunately, after a little hard work, you find a way to improve the process. However, you want to perform the appropriate statistical analysis to back up your findings and make it easier to explain the process improvements to your boss. And it's important to remember that your boss is much like the boss... 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
Using data analysis and statistics to improve business quality has a long history. But it often seems like most of that history involves huge operations. After all, Six Sigma originated with Motorola, and became adopted by thousands of other businesses after it was adopted by a little-known outfit called General Electric. There are many case studies and examples of how big companies used Six Sigma... 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
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
Making parts that are truly interchangeable is a critical aspect of modern manufacturing. The same parts may be manufactured in different plants spread around the globe or by suppliers located far away. Parts need to be manufactured to specifications to ensure that they are almost identical to allow an easy assembly of new products. Interchangeability is increasingly important in the... Continue Reading
by Matthew Barsalou, guest blogger The field of statistics has a long history and many people have made contributions over the years. Many contributors to the field were educated as statisticians, such as Karl Pearson and his son Egon Pearson. Others were people with problems that needed solving, and they developed statistical methods to solve these problems. The Standard Normal Distribution One... Continue Reading
by Dan Wolfe, guest blogger How would you measure a hole that was allowed to vary one tenth the size of a human hair? What if the warmth from holding the part in your hand could take the measurement from good to bad? These are the types of problems that must be dealt with when measuring at the micron level. As a Six Sigma professional, that was the challenge I was given when Tenneco entered into... 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
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