Performing a Short-Term Study

Performing a Short-Term Study

Gauging your conformance decisions

n the past couple of articles, we have been having fun together testing whether a measurement device is usable for the crazy purpose of determining if we are actually making product in or out of specification. Last month, we performed a measurement systems analysis (MSA) “potential study” using a snazzy MSA spreadsheet (if I do say so myself)*. We found that the Hard-A-Tron was not only pretty highly variable (compared to our spec), but that the material we were measuring actually might have been changing over time. But a potential study was not enough for you, was it? You asked, nay demanded, that we perform a short-term MSA, and I, your humble servant, gave you the data to do so. After the jump, we will perform the analysis, so unless you are the type of person that flips to the back of the book to see if you want to read it, finish up your analysis, and then click to read more.

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Performing a Long-Term MSA

Performing a Long-Term MSA

Testing through time stability

Ahh, measurement system analysis—the basis for all our jobs because, as Lord Kelvin said, “… When you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.” How interesting it is then, that we who thrive on data so frequently don't have any proof that the numbers we're using relate to the event we are measuring—hence my past few articles about the basics of measurement system analysis in “Letting You In on a Little Secret,” on how to do a potential study in “The Mystery Measurement Theatre, and on how to do a short-term study in “Performing a Short-Term MSA Study.” The only (and most important) topic remaining is how to perform a long-term study, which is the problem I left with you last month.

So read on to see how.

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Destructive Gauges and Measurement System Analysis

Destructive Gauges and Measurement System Analysis

Can they co-exist?

We have recently covered a lot of ground on the topic of measurement system analysis (MSA). We talked about the basics of MSA, the potential study, the short-term study, and the long-term study. At this point you should have a pretty firm foundation in the importance and methods of good MSA studies for your research and production, as well as a practical tool to help you in doing measurement system analysis—the file "MSA Forms 3.22.xls" (gauge repeatability and reproducibility worksheets)— which is a free download from Six Sigma Online. In this article, I am going to tie up some loose ends and then talk about a frequent question, “Is MSA even possible with a destructive gauge?”

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Know the Process Before Altering Its Specifications

Know the Process Before Altering Its Specifications

You must balance risk and benefits when determining acceptability.

So I thought I was done with measurement system analysis after my last column, but I just finished reading Don Wheeler’s June 1 column, “Is the Part in Spec?” and the first thing I thought was, “Well, that was… complicated and ultimately unhelpful in answering the article’s title question.” I like a diversity of viewpoints, but they have to make sense. Does Wheeler’s? Let’s take a closer look.

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The Omnipotence of Random Sampling Distributions

The Omnipotence of Random Sampling Distributions

Every answer to statistical problems lies within RSD

As I was teaching class the other day, I told the students I was going to reveal to them the one secret they needed to learn to understand every statistical test they would ever use. The secret was the one thing that would make statistics more of a reasonable science than a bunch of equations to memorize, the one thing they needed to pass my class. (OK, there is a lot more needed to pass the class, but without this one thing doing so is a lot harder.)

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(Sample) Size Matters

(Sample) Size Matters

Random sampling distribution are really something delightful

Last month I wrote about how the random sampling distribution (RSD) of various sample statistics are the basis for pretty much everything in statistics. If you understand RSDs, you understand a lot about why we do what we do in hypothesis testing, inferential statistics, and estimation of confidence intervals. Understanding RSDs gives you a huge advantage as you seek to use data in business, so let's take a closer look.

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Making Decisions in a Non-Normal World

Making Decisions in a Non-Normal World

The power of the central limit theorem

Throughout the last couple of articles, I have explained and illustrated that understanding the random sampling distribution (RSD) of a statistic is key to understanding the entire basis of inferential statistics. Which is just a fancy way of saying “avoiding career-terminating decisions.” This month I’ll show you how the central limit theorem is your best friend, statistically speaking.

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