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# How to Conduct a Measurement Systems Analysis (MSA), Part One

As promised a few posts ago, I’d like to explain exactly how to go about completing a measurement systems analysis (MSA).

If the sound of this makes you want to yawn… well… stop it! It’s Monday and time to get focused (and some coffee).   Seriously, this one tool has greatly benefited me over the years and I know it will you too.

The two pre-cursor articles to this one explained one such example of a variation story and how a simple MSA helped save millions of dollars in 60 minutes.

Now then, tonight I want to begin by explaining what a measurement system analysis is as well as two types of MSA that will serve you very well once you’ve mastered them.

MSA Defined (Job Interview Proof)

Right, so if you’re ever on a job interview and get asked to explain what an MSA is you would probably do well to rattle off something like this:

A Measurement System Analysis, abbreviated MSA, is a specially designed experiment that seeks to identify the components of variation in the measurement.

That would be the Wikipedia definition and I guess it sounds pretty nice… and chances are the guy interviewing won’t have a clue himself… so, yeah, this would be a great answer!

MSA Defined (Ron’s Take)

But listen, I’m a simple man. So rather than getting all text book like allow me to offer my explanation of what a MSA is. You see, anytime we measure something (e.g. the weight of a part) we’re actually dealing with two types of variation.

1. The variation within the parts/process we’re studying (P)
2. The variation within the measurement system itself (M)

In other words, the total variation we’re experiencing (T) can be explained by a formula that looks something like this: T = P + M.

In a perfect world the variation due to M (measurement system) would be zero meaning all we need to do is attack and defeat the variation within the process (P) and then ride off victorious.

Sadly, many times there is so much variation with the actual measurement system we have no earthly clue how much variation is due to the actual process.  Even worse, we may try and try and try to improve the process only to find out the problem wasn’t even the process… it was the dang measurement system!

And this is precisely why measurement systems analysis is so important. We must identify how much of the total variation is due to the process and how much is due to the actual measurement system.

Types of MSA

There are different types of MSA out there and the one you choose has a lot to do with the data you’re dealing with.

• When dealing with variable data (data we can measure like weight, distance, etc.) a Gage R&R study will serve you well. This stands for Gage Repeatability & Reproducibility.
• When dealing with attribute data (pass/fail, good/bad, etc.) an Attribute Gage study will do the trick nicely.

Up Next

Now that we know what a MSA is as well as two popular types of analysis it’s time to learn how to conduct the actual studies… and that’s precisely what we’ll discuss in the very near future!

If you have any experience, good or bad, with measurement systems analysis please share in the comments section below.  Also, if you have a specific question on the topic please share that as well.

1. SOUJANYA says:

very nice

2. Excellent

3. Glenn says:

Where is the entire article?

4. KKUMAR says:

A very nice and simple explanation for MSA.Thank you for cotributing this article on the net.

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