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Continuous Quality Improvement

Blog posts and articles that pertain to continuous quality improvement methods, including Lean and Six Sigma.

Companion by Minitab® is our software for executing and reporting on quality improvement projects. It consists of a desktop app, which practitioners use to do project work, and a web app, which includes a customizable dashboard that offers stakeholders up-to-the-minute graphical summaries and reports. Since the desktop app automatically updates the dashboard as teams do their work, teams are freed... Continue Reading
Companion by Minitab® is our software for executing and reporting on quality improvement projects. It has two components, a desktop app and a web app. As practitioners use the Companion desktop app to do project work, their project information automatically rolls up to Companion’s web app dashboard, where stakeholders can see graphical summaries and reports. Since the dashboard updates... Continue Reading

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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
By now you have probably heard about Companion by Minitab®, our software for executing and reporting on quality improvement projects. We've had questions about some terminology used in the product, which has two main components: the desktop application, or desktop app for short, and the web application, or web app for short, but also sometimes referred to as the full version or subscription. If... Continue Reading
Rare events inherently occur in all kinds of processes. In hospitals, there are medication errors, infections, patient falls, ventilator-associated pneumonias, and other rare, adverse events that cause prolonged hospital stays and increase healthcare costs.  But rare events happen in many other contexts, too. Software developers may need to track errors in lines of programming code, or a quality... Continue Reading
In Part 1 of my A New Spin on the "Stand in a Circle" Exercise blog, I described how Taiichi Ohno, the creator of the Toyota Production System, used the “Stand in a Circle” exercise to help managers identify waste in their operations.  During this exercise Ohno would take a manager or student to the shop floor, draw a chalk circle on the floor, then have them stand inside the circle and observe an... Continue Reading
In the mid 1940s, Taiichi Ohno established the Toyota Production System, which is primarily based on eliminating non-value-added waste. He discovered that by reducing waste and inventory levels, problems get exposed and that forces employees to address these problems. To engage the workers and therefore improve processes, Ohno developed many exercises. One of his most popular exercises, “Stand in a... Continue Reading
One of the most memorable presentations at the inaugural Minitab Insights conference reminded me that data analysis and quality improvement methods aren't only useful in our work and businesses: they can make our home life better, too.  The presenter, a continuous improvement training program manager at an aviation company in the midwestern United States, told attendees how he used Minitab... Continue Reading
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 lostFor want of a rider the battle was lostFor want of a battle the kingdom was lostAnd 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... Continue Reading
"Data! Data! Data! I can't make bricks without clay."  — Sherlock Holmes, in Arthur Conan Doyle's The Adventure of the Copper Beeches Whether you're the world's greatest detective trying to crack a case or a person trying to solve a problem at work, you're going to need information. Facts. Data, as Sherlock Holmes says.  But not all data is created equal, especially if you plan to analyze as part of... Continue Reading
Do your executives see how your quality initiatives affect the bottom line? Perhaps they would more often if they had accessible insights on the performance, and ultimately the overall impact, of improvement projects.  For example, 60% of the organizations surveyed by the American Society for Quality in their 2016 Global State of Quality study say they don’t know or don’t measure the financial... Continue Reading
Did you know the most popular diamond cut is probably the Round Brilliant Cut? The first early version of what would become the modern Round Brilliant Diamond Cut was introduced by an Italian named Vincent Peruzzi, sometime in the late 17th century.  In the early 1900s, the angles for an "ideal" diamond cut were designed by Marcel Tolkowsky. Minor changes have been made since then, but the angles... Continue Reading
In its industry guidance to companies that manufacture drugs and biological products for people and animals, the Food and Drug Administration (FDA) recommends three stages for process validation. While my last post covered statistical tools for the Process Design stage, here we will focus on the statistical techniques typically utilized for the second stage, Process Qualification. Stage 2: Process... Continue Reading
In my last post on DMAIC tools for the Define phase, we reviewed various graphs and stats typically used to define project goals and customer deliverables. Let’s now move along to the tools you can use in Minitab Statistical Software to conduct the Measure phase. Measure Phase Methodology The goal of this phase is to measure the process to determine its current performance and quantify the problem.... Continue Reading
If you’re familiar with Lean Six Sigma, then you’re familiar with DMAIC. DMAIC is the acronym for Define, Measure, Analyze, Improve and Control. This proven problem-solving strategy provides a structured 5-phase framework to follow when working on an improvement project. This is the first post in a five-part series that focuses on the tools available in Minitab Statistical Software that are most... Continue Reading
The ultimate goal of most quality improvement projects is clear: reducing the number of defects, improving a response, or making a change that benefits your customers. We often want to jump right in and start gathering and analyzing data so we can solve the problems. Checking your measurement systems first, with methods like attribute agreement analysis or Gage R&R, may seem like a needless waste... Continue Reading
It's been called a "demographic watershed".  In the next 15 years alone, the worldwide population of individuals aged 65 and older is projected to increase more than 60%, from 617 million to about 1 billion.1 Increasingly, countries are asking themselves: How can we ensure a high quality of care for our growing aging population while keeping our healthcare costs under control? The answer? More... Continue Reading
My previous post covered the initial phases of a project to attract and retain more patients in a cardiac rehabilitation program, as described in a 2011 Quality Engineering article. A Pareto chart of the reasons enrolled patients left the program indicated that the hospital could do little to encourage participants to attend a greater number of sessions, so the team focused on increasing initial... Continue Reading
This is an era of massive data. A huge amount of data is being generated from the web and from customer relations records, not to mention also from sensors used in the manufacturing industry (semiconductor, pharmaceutical, petrochemical companies and many other industries). Univariate Control Charts In the manufacturing industry, critical product characteristics get routinely collected to ensure... Continue Reading
In the first part of this series, we looked at a case study where staff at a hospital used ATP swab tests to test 8 surfaces for bacteria in 10 different hospital rooms across 5 departments. ATP measurements below 400 units pass the swab test, while measurements greater than or equal to 400 units fail the swab test and require further investigation. I offered two tips on exploring and visualizing... Continue Reading