Quality Improvement

Blog posts and articles about using statistics and to improve quality through methods such as Lean and Six Sigma.

As we start off 2018, our eyes are on the winter weather, specifically low temperatures and snowfall. After 2015-2016's warmest winter on record and Chicago breaking records in 2017 with no snow sticking to the ground in January or February, our luck might have run out. We shall see, though. The Old Farmer's Almanac is reporting that 2017-2018 winter temperatures will be colder than last winter. If... Continue Reading
Dramatic cost savings. Lead time and inventory reductions. Improved transactional processes. Although Lean has its roots in manufacturing, nearly every industry and type of organization around the world can benefit from it. A little while back, we reviewed 5 Critical Lean Tools that are a great way to get started implementing Lean. Today, let’s continue with 5 More Critical Lean Tools.  1. Kaizen Kai... Continue Reading
Editor's note: If you would like to see these tools presented in a webinar, visit our On Demand Webinars and look for "5 Critical Tools for Your Lean Deployment." Lean, also known as “Lean Manufacturing” or “Lean Production,” focuses on maximizing customer value by removing waste and eliminating defects. Lean tools are about understanding the process, looking for waste, preventing mistakes and... Continue Reading
On the heels of Healthcare Quality Week last week, we wanted to share our conversation with Dr. Sandy Fogel, the surgical quality officer at Carilion Clinic in Roanoke, VA. Although he has been a practicing surgeon for nearly 40 years, Dr. Fogel’s enthusiasm for quality improvement makes it sound as if he is just getting started. After medical school at Washington University in St. Louis and... Continue Reading
Research out of the Juran Institute, which specializes in training, certification, and consulting on quality management globally, reveals that only 30 percent of improvement initiatives succeed.   And why do these initiatives fail so frequently? This research concludes that a lack of management support is the No. 1 reason quality improvement initiatives fail. But this is certainly not a problem... Continue Reading
Overfitting a model is a real problem you need to beware of when performing regression analysis. An overfit model result in misleading regression coefficients, p-values, and R-squared statistics. Nobody wants that, so let's examine what overfit models are, and how to avoid falling into the overfitting trap. Put simply, an overfit model is too complex for the data you're analyzing. Rather than... Continue Reading
Control charts take data about your process and plot it so you can distinguish between common-cause and special-cause variation. Knowing the difference is important because it permits you to address potential problems without over-controlling your process.   Control charts are fantastic for assessing the stability of a process. Is the process mean unstable, too low, or too high? Is observed... Continue Reading
In statistics, as in life, absolute certainty is rare. That's why statisticians often can't provide a result that is as specific as we might like; instead, they provide the results of an analysis as a range, within which the data suggest the true answer lies. Most of us are familiar with "confidence intervals," but that's just of several different kinds of intervals we can use to characterize the... Continue Reading
by Matthew Barsalou, guest blogger At the end of the first part of this story, a group of evil trouble-making chickens had convinced all of their fellow chickens to march on the walled city of Wetzlar, where, said the evil chickens, they all would be much happier than they were on the farm. The chickens marched through the night and arrived at Wetzlar on the Lahn as the sun came up. “Let us in!”... Continue Reading
by Matthew Barsalou, guest blogger Once upon a time, in the Kingdom of Wetzlar, there was a farm with over a thousand chickens, two pigs, and a cow. The chickens were well treated, but a few rabble-rousers among them got the rest of the chickens worked up. These trouble-making chickens looked almost like the other chickens, but in fact they were evil chickens.  By HerbertT - Eigenproduktion, CC... Continue Reading
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
In April 2017, overbooking of flight seats hit the headlines when a United Airlines customer was dragged off a flight. A TED talk by Nina Klietsch gives a good, but simplistic explanation of why overbooking is so attractive to airlines. Overbooking is not new to the airlines; these strategies were officially sanctioned by The American Civil Aeronautics Board in 1965, and since that time complex... Continue Reading
Can you trust your data?  That's the very first question we need to ask when we perform a statistical analysis. If the data's no good, it doesn't matter what statistical methods we employ, nor how much expertise we have in analyzing data. If we start with bad data, we'll end up with unreliable results. Garbage in, garbage out, as they say. So, can you trust your data? Are you positive?... Continue Reading
All processes have variation, some of which is inherent in the process, and isn't a reason for concern. But when processes show unusual variation, it may indicate a change or a "special cause" that requires your attention.  Control charts are the primary tool quality practitioners use to detect special cause variation and distinguish it from natural, inherent process variation. These charts graph... Continue Reading
If you have a process that isn’t meeting specifications, using the Monte Carlo simulation and optimization tools in Companion by Minitab can help. Here’s how you, as an engineer in the medical device industry, could use Companion to improve a packaging process and help ensure patient safety. Your product line at AlphaGamma Medical Devices is shipped in heat-sealed packages with a minimum seal... Continue Reading
How many samples do you need to be “95% confident that at least 95%—or even 99%—of your product is good? The answer depends on the type of response variable you are using, categorical or continuous. The type of response will dictate whether you 'll use: Attribute Sampling: Determine the sample size for a categorical response that classifies each unit as Good or Bad (or, perhaps, In-spec or... Continue Reading
My previous post focused on manipulating text data using Minitab’s calculator. In this post we continue to explore some of the useful tools for working with text data, and here we’ll focus on Minitab’s Data menu. This is the second in a 3-part series, and in the final post we’ll look at the new features in Minitab’s Editor menu. Using the Data Menu When I think of the Data menu, I think... Continue Reading
It’s usually not a good idea to rely solely on a single statistic to draw conclusions about your process. Do that, and you could fall into the clutches of the “duck-rabbit” illusion shown here: If you fix your eyes solely on the duck, you’ll miss the rabbit—and vice-versa. If you're using Minitab Statistical Software for capability analysis, the capability indices Cp and Cpk are good examples of... 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