Statistical Process Control

Blog posts and articles about using statistics and data analysis to control a process and ensure quality.

Before cutting an expensive piece of granite for a countertop, a good carpenter will first confirm he has measured correctly. Acting on faulty measurements could be costly. While no measurement system is perfect, we rely on such systems to quantify data that help us control quality and monitor changes in critical processes. So, how do you know whether the changes you see are valid and not just the... Continue Reading
The 1949 film A Connecticut Yankee in King Arthur's Court includes the song “Busy Doing Nothing,” and this could be written about the Null Hypothesis as it is used in statistical analyses.  The words to the song go: We're busy doin' nothin'Workin' the whole day through Tryin' to find lots of things not to do And that summarises the role of the Null Hypothesis perfectly. Let me explain why. What's... Continue Reading


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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
As a member of Minitab's Technical Support team, I get the opportunity to work with many people creating control charts. They know the importance of monitoring their processes with control charts, but many don’t realize that they themselves could play a vital role in improving the effectiveness of the control charts.   In this post I will show you how to take control of your charts by using Minitab... Continue Reading
As someone who has collected and analyzed real data for a living, the idea of using simulated data for a Monte Carlo simulation sounds a bit odd. How can you improve a real product with simulated data? In this post, I’ll help you understand the methods behind Monte Carlo simulation and walk you through a simulation example using Companion by Minitab. Companion by Minitab is a software platform that... Continue Reading
Choosing the right type of subgroup in a control chart is crucial. In a rational subgroup, the variability within a subgroup should encompass common causes, random, short-term variability and represent “normal,” “typical,” natural process variations, whereas differences between subgroups are useful to detect drifts in variability over time (due to “special” or “assignable” causes). Variation within... 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
Earlier, I wrote about the different types of data statisticians typically encounter. In this post, we're going to look at why, when given a choice in the matter, we prefer to analyze continuous data rather than categorical/attribute or discrete data.  As a reminder, when we assign something to a group or give it a name, we have created attribute or categorical data.  If we count something, like... 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
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: Process Design, Process Qualification, and Continued Process Verification. In this post, we we will focus on that third stage. Stage 3: Continued Process Verification Per the FDA guidelines, the goal of... Continue Reading
People can make mistakes when they test a hypothesis with statistical analysis. Specifically, they can make either Type I or Type II errors. As you analyze your own data and test hypotheses, understanding the difference between Type I and Type II errors is extremely important, because there's a risk of making each type of error in every analysis, and the amount of risk is in your control.    So if... Continue Reading
Welcome to the Hypothesis Test Casino! The featured game of the house is roulette. But this is no ordinary game of roulette. This is p-value roulette! Here’s how it works: We have two roulette wheels, the Null wheel and the Alternative wheel. Each wheel has 20 slots (instead of the usual 37 or 38). You get to bet on one slot. What happens if the ball lands in the slot you bet on? Well, that depends... Continue Reading
A recent discussion on the Minitab Network on LinkedIn pertained to the I-MR chart. In the course of the conversation, a couple of people referred to it as "The Swiss Army Knife of control charts," and that's a pretty great description. You might be able to find more specific tools for specific applications, but in many cases, the I-MR chart gets the job done quite adequately. When you're... Continue Reading
Right now I’m enjoying my daily dose of morning joe. As the steam rises off the cup, the dark rich liquid triggers a powerful enzyme cascade that jump-starts my brain and central nervous system, delivering potent glints of perspicacity into the dark crevices of my still-dormant consciousness. Feels good, yeah! But is it good for me? Let’s see what the studies say… Drinking more than 4 cups of coffee... Continue Reading
To make objective decisions about the processes that are critical to your organization, you often need to examine categorical data. You may know how to use a t-test or ANOVA when you’re comparing measurement data (like weight, length, revenue, and so on), but do you know how to compare attribute or counts data? It easy to do with statistical software like Minitab.  One person may look at this bar... Continue Reading
by Rehman Khan, guest blogger There are many articles giving Minitab tips already, so to be different I have done mine in the style of my books, which use example-based learning. All ten tips are shown using a single example. If you don’t already know these 10 tips you will get much more benefit if you work along with the example. You don’t need to download any files to work along—although, if you... Continue Reading
Have you ever wanted to know the odds of something happening, or not happening?  It's the kind of question that students are frequently asked to calculate by hand in introductory statistics classes, and going through that exercise is a good way to become familiar with the mathematical formulas the underlie probability (and hence, all of statistics).  But let's be honest: when class is over, most... Continue Reading
Have you ever wished your control charts were better?  More effective and user-friendly?  Easier to understand and act on?  In this post, I'll share some simple ways to make SPC monitoring more effective in Minitab. Common Problems with SPC Control Charts I worked for several years in a large manufacturing plant in which control charts played a very important role. Virtually thousands of SPC... Continue Reading
by Matthew Barsalou, guest blogger The great Dr. Seuss tells of Mr. Plunger, who is the custodian at Diffendoofer School on the corner of Dinkzoober and Dinzott in the town of Dinkerville. The good Mr. Plunger “keeps the whole school clean” using a supper-zooper-flooper-do. Unfortunately, Dr. Seuss fails to tell us where the supper-zooper-flooper-do came from and if the production process was... 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