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Lean Six Sigma

Blog posts and articles about applying data analysis and statistical methods to Lean Six Sigma projects.

The Six Sigma quality improvement methodology has lasted for decades because it gets results. Companies in every country around the world, and in every industry, have used this logical, step-by-step method to improve the quality of their processes, products, and services. And they've saved billions of dollars along the way. However, Six Sigma involves a good deal of statistics and data analysis,... Continue Reading
Six Sigma is a quality improvement method that businesses have used for decades—because it gets results. A Six Sigma project follows a clearly defined series of steps, and companies in every industry in every country around the world have used this method to resolve problems. Along the way, they've saved billions of dollars. But Six Sigma relies heavily on statistics and data analysis, and many... Continue Reading
For a process improvement practitioner, finishing the Control Phase of the DMAIC process is your ticket to move on to your next project. You’ve done an excellent job leading the project team because they identified root causes, developed and implemented solutions to resolve those root causes, put a control plan in place and transitioned the process back to the Process Owner. Soon, however, you... Continue Reading
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
It's a very exciting time at Minitab's offices around the world because we've just announced the availability of Minitab® 18 Statistical Software. Data is everywhere today, but to use it to make sound, strategic business decisions, you need to have tools that turn that data into knowledge and insights. We've designed Minitab 18 to do exactly that.  We've incorporated a lot of new features, made some... Continue Reading
Control charts are excellent tools for looking at data points that seem unusual and for deciding whether they're worthy of investigation. If you use control charts frequently, then you're used to the idea that if certain subgroups reflect temporary abnormalities, you can leave them out when you calculate your center line and control limits. If you include points that you already know are... 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
By some estimates, up to 70 percent of quality initiatives fail. Why do so many improvement programs, which are championed and staffed by smart, dedicated people, ultimately end up on the chopping block? According to the Juran Institute, which specializes in training, certification, and consulting on quality management, the No. 1 reason quality improvement initiatives fail is a lack of management... 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
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
In Parts 1 and 2 of Gauging Gage we looked at the numbers of parts, operators, and replicates used in a Gage R&R Study and how accurately we could estimate %Contribution based on the choice for each.  In doing so, I hoped to provide you with valuable and interesting information, but mostly I hoped to make you like me.  I mean like me so much that if I told you that you were doing... Continue Reading
You run a capability analysis and your Cpk is bad. Now what? First, let’s start by defining what “bad” is. In simple terms, the smaller the Cpk, the more defects you have. So the larger your Cpk is, the better. Many practitioners use a Cpk of 1.33 as the gold standard, so we’ll treat that as the gold standard here, too. Suppose we collect some data and run a capability analysis using Minitab Statisti... Continue Reading
In Part 1 of Gauging Gage, I looked at how adequate a sampling of 10 parts is for a Gage R&R Study and providing some advice based on the results. Now I want to turn my attention to the other two factors in the standard Gage experiment: 3 operators and 2 replicates.  Specifically, what if instead of increasing the number of parts in the experiment (my previous post demonstrated you would need... Continue Reading
by Kevin Clay, guest blogger In transactional or service processes, we often deal with lead-time data, and usually that data does not follow the normal distribution. Consider a Lean Six Sigma project to reduce the lead time required to install an information technology solution at a customer site. It should take no more than 30 days—working 10 hours per day Monday–Friday—to complete, test and... Continue Reading
"You take 10 parts and have 3 operators measure each 2 times." This standard approach to a Gage R&R experiment is so common, so accepted, so ubiquitous that few people ever question whether it is effective.  Obviously one could look at whether 3 is an adequate number of operators or 2 an adequate number of replicates, but in this first of a series of posts about "Gauging Gage," I want to look at... Continue Reading
In Part 1 of this blog series, I compared Six Sigma to a diamond because both are valuable, have many facets and have withstood the test of time. I also explained how the term “Six Sigma” can be used to summarize a variety of concepts, including philosophy, tools, methodology, or metrics. In this post, I’ll explain short/long-term variation and between/within-subgroup variation and how they help... 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