William A. Levinson
IATF 16949:2016 clause 7.1.5.1.1 requires measurement systems analysis (MSA) to quantify gage and instrument variation. The deliverables of the generally accepted procedure are the repeatability or...
Saligrama Agnihothri
Health-tracking devices and apps are becoming part of everyday life. More than 300,000 mobile phone applications claim to help with managing diverse personal health issues, from monitoring blood...
Donald J. Wheeler
Your software routinely gives you four descriptive statistics for your data: the average, the standard deviation, the skewness, and the kurtosis. Of these only the average is easy to understand. This...
William A. Levinson
The first part of this series introduced measurement systems analysis for attribute data, or attribute agreement analysis. AIAG1 provides a comprehensive overview, and Jd Marhevko2 has done an...
Donald J. Wheeler
Measurement error is ubiquitous. As a result, over the past 250 years, different areas of science and engineering have come up with many different ways to deal with the problem of measurement...
James Bossert
When we talk about measurement system analysis (MSA), people tend to focus on attribute agreement analysis because it is usually quicker and easier to do than a gauge repeatability and...
William A. Levinson
Measurement systems analysis (MSA) for attributes, or attribute agreement analysis, is a lot like eating broccoli or Brussels sprouts. We must often do things we don't like because they are necessary...
Ryan McKenna
To date, this series focused on relatively simple data analyses, such as learning one summary statistic about our data at a time. In reality, we’re often interested in a slightly more sophisticated...
Donald J. Wheeler
For more than 40 years it has been common to use the precision to tolerance ratio (P/T ratio) to compare the standard deviation of measurement error with the specified tolerance for a...
David Darais
In our last article, we discussed how to determine how many people drink pumpkin spice lattes in a given time period without learning their identifying information. But say, for example, you would...
Donald J. Wheeler
In my article, “Tightened 100% Inspection” (Quality Digest, March 29, 2021), we found that the excess costs associated with tightened specification limits are generally prohibitive. Here we...
David Darais
How many people drink pumpkin spice lattes in October, and how would you calculate this without learning specifically who is drinking them, and who is not?
Although they seem simple or trivial,...
Donald J. Wheeler
Inspection sounds simple. Screen out the bad stuff and ship the good stuff. However, measurement error will always create problems of misclassification where good stuff is rejected, and bad stuff...
Scott A. Hindle
A quick Google search returns many instances of the saying, “A man with a watch knows what time it is. A man with two watches is never sure.” The doubt implied by this saying extends to manufacturing...
William A. Levinson
Traditional statistical methods for computing the process performance index (Ppk) and control limits for process-control purposes assume that measurements are available for all items or parts. If,...
Fred Schenkelberg
There is a type of error that occurs when conducting statistical testing: to work very hard to correctly answer the wrong question. This error occurs during the formation of the experiment.
Despite...
Adam Conner-Simons
This story was originally published by MIT Computer Science & Artificial Intelligence Lab (CSAIL).
Scatterplots. You may not know them by name, but if you spend more than 10 minutes online, you’...
Jay Arthur—The KnowWare Man
There are two ways to increase profits: increase sales or reduce costs. Although most data analysis seeks to find more ways to sell more stuff to more people, addressing preventable problems is an...
Matthew Bundy
Untitled Document
Burning plastic cart carrying a fax machine, a laptop computer, and a three-ring binder. Click here for larger image. Credit: FCD/NIST
Several centuries ago, scientists...
Douglas Allen
Any number derived from real observation is made up of three components. The first of these is the intended signal, the “perfect” value from the object being observed. The second is error (or noise)...
