When I first got involved with quality, I learned about the “five M’s” that constituted most root causes: man, machine, materials, methods, and measurement. In manufacturing you know that measurement gages and how they are used can be a key cause of variation.

Accuracy and repeatability is the lifeblood of all CMMs. If they aren’t accurate, there’s no point in having them. However, the degree of accuracy required is dependent on the particular application. For manufacturing gas turbines and aircraft engines, a very high degree of accuracy is often required.

Many quality engineers don’t know the Gage Repeatability and Reproducibility, or Gage R&R, of their leak test. Many, frankly, don’t want to know because they fear how poor it may be.

Have you ever stepped on a scale to weigh yourself, stepped off the scale, and then stepped back on to measure your weight a second time? Have you ever gotten two different readings?

Spending too much (time or money) on part disposition? Start with an analysis of your measurement system. Even a marginal measurement system could contribute up to 30% of the variation seen in your control chart.

Height gages have achieved a nearly universal presence in the quality control world. It is rare to see a QC department without at least one or two of these instruments. This commonality makes it easy to overlook just how accurate and flexible these devices are. They measure much more than the term “height gage” would imply.

It’s certainly not news that more and more gages are being forced out onto the shop floor. Tight tolerance measurements that were once performed by a trained inspection technician are now being done right next to the machining center, most likely by the machine tool operator.

Most improvement projects have a goal—like reducing defects. Teams often want to jump in and start gathering data so they can solve the problems. Checking measurement systems first may seem like a waste of time, but a Gage R&R study is a critical step in any analysis involving continuous data.

One of the questions our applications team is most commonly asked is “Why aren’t my systems producing the exact same results?”