## Fun With Measurement Systems Analysis – Part 1

By Ron Pereira

Over the years I’ve been fortunate to visit many different companies across the world.  During these visits I’ve seen some amazing examples of continuous improvement in action.

But, to be blunt, there is one aspect of continuous improvement I simply don’t see practiced enough – measurement systems analysis.

### Variation

Being able to attack variation is an extremely important aspect of continuous improvement. But variation is a tricky opponent. The variation we see isn’t always what we think it is.  Allow me to explain with a simple diagram (click picture to enlarge it).

At the top, we see the observed process variation. In other words, this is the data that we’d use to conduct a Process Capability Study where obviously, we’re interested in understanding how our process variation is behaving.

Unfortunately, there are two things that make up our total observed process variation, the actual process variation and the measurement variation. Put another way, it’s entirely possible that the variation we’re observing is mostly due to the measurement system and continuing to attack the actual process variation won’t help at all.

Our actual process variation consists of short-term, long-term, and part-to-part variation. Measurement variation consists of several characteristics including accuracy, repeatability, reproducibility, stability, and resolution.

### Measurement System Characteristics

Let’s spend some time discussing each of these important measurement system characteristics.

First, accuracy is the ability of the gage to measure the true value of a part on average.  In other words, it’s possible for a measurement system to have high variability but still be accurate so long as the average value of the measurements are close to the true value.

Next, repeatability, which is a component of precision, is attained when the same person takes multiple measurements and gets the same, or similar, results each time.

A close cousin to repeatability is reproducibility, the second component of Precision. Reproducibility is attained when other people get the same, or similar results, you do when measuring the same item.

While repeatability focuses on how well you measure something, reproducibility compares your measurement performance to other people’s measurement performance.

Next, stability is attained when measurements taken by the same person, or gage, vary little over time. In other words, it shouldn’t matter what day of the week or time of day it is. We should always be able to measure in an accurate and repeatable manner.

Last, but certainly not least, sufficient resolution means that your measurement system provides at least five, more preferably, distinct values in the range you’re measuring.

### Sufficient Resolution

For example, let’s say we wanted to measure the heights of three children with a scale that only measures to the nearest foot. When we did this, our results were 3 feet for child one, 4 feet for child two, and 5 feet for child three. In other words, we only had three distinct values.

As it turns out, the key to ensuring we have adequate resolution is by determining the amount of discrimination our scale needs.  Discrimination refers to the number of decimal places that can be measured by the system.  Increments of measure should be approximately one‐tenth of the width of the product specification or process variation.

For example, let’s say that we’re working with a process that has an upper customer specification limit of 80 mm and a lower customer specification limit of 60 mm.

When we subtract 60 from 80, we learn that our tolerance is 20 mm. In other words, this measurement system needs to be able to discriminate to at least 2 mm since 20 mm divided by 10 is 2 mm.

### Measurement Systems Analysis

We’ve covered a lot of terms and concepts so far which may make you feel a little overwhelmed. The good news is we have an extremely powerful tool at our disposal that wraps everything that we’ve discussed up into a single statistical tool called Measurement Systems Analysis, or MSA for short.