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If you’re becoming familiar with Six Sigma, it’s only a matter of time before you learn about MSA (Measurement System Analysis). This concept is right at home finding and eliminating potential variability. As we’re going to cover in detail below, there are certain levels of MSAs. By learning them now, you’ll have a much easier time using them in the future.

The Importance of Experimentation:
One very important tenet to grasp when it comes to MSA is that of experimentation. It’s at the core of this concept, but it’s also something that a lot of business people feel challenged by. After all, a poorly designed, executed or though-out experiment could produce truly dire consequences.
The good news is that, like so much else in the world of Six Sigma, MSA experiments follow certain guidelines that virtually ensure they’ll produce a positive result – namely, to identify any variation in your business processes.

Finding Variations:
Speaking of which, the purpose of MSA is to find where there are variations taking place. Specifically, MSA was designed to seek out these variations in processes that obtain measurements and data. As these variations run the risk of producing major problems, it’s important that they are found and fixed ASAP.

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A Focus on Measurements:
We’ve already touched on this, but the main focus of an MSA is on measurements. However, this entails a few other elements. There are measuring instruments, test methods and the process for obtaining the very measurements.
The reason why it’s so important to use an MSA for this purpose should be pretty self-evident. To put it simply, if you can’t trust the measurements you are using, you can’t trust the results.
Aside from the defects we already mentioned, think about all the time and money that could be wasted because of these accidents.
Other areas that an MSA can be used to hunt for defects are procedures, operations, equipment, software and even workers.

General Rules:
Sometimes, when people talk about the levels of MSA, they’re being very literal. There are actual levels of measurement compliance that have corresponding interpretations.

That list looks like this:
• 10% or fewer errors is acceptable.
• Between 10% and 30% errors means that the system is probably acceptable, though this would depend on the cost of the measuring device, the price for repairs and the important of the actual application. Other factors may be included, too.
• More than 30% errors would be considered unacceptable. If your MSA returned these results, you’d want to work on the measurement system right away. Furthermore, some organizations believe that the number of categories that the measurement protocols divides a business process into should be at least five.
You’ll have to consider the unique aspects of your business when using MSA, but the above explanation should work.

Controls:
Finally, as you can imagine, it is important that the way an MSA works remains consistent. Otherwise, it would become part of the potential problem.

To this end, the following requirements should be met by an MSA:
• Long-term statistical stability
• Small variability compared to process variability
• Small variability compared to the specification limits
• The solution of the measurement device needs to be small compared to the smaller of either the process spread or specification tolerance.

A good rule of thumb when using an MSA is that the measurement system’s resolution should be 90% of the process spread or specification tolerance, at most.

Though an MSA can involve a number of different moving parts, the above should give you a pretty good idea of why they are such powerful solutions. Furthermore, like anything, the more you practice using them, the easier it will become to do so.

Sources:

Measurement System Analysis – MSA

https://www.moresteam.com/toolbox/measurement-system-analysis.cfm

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