In a gauge R&R study, what does a high percent gage R&R indicate?

In a gauge R&R study, what does a high percent gage R&R indicate?

• A. The measurement system has high variability and is not reliable for decisions.
• B. The measurement system is highly precise and repeatable.
• C. The measurement system is perfectly unbiased.
• D. The measurement system has zero gage R&R.

Answer: (A)

Gauge R&R shows how much of the total observed variation comes from the measurement system itself, by separating part-to-part variation from the noise introduced by the gage, including both repeatability and reproducibility. When the percent gage R&R is high, the measurement process is introducing a lot of variability relative to the actual differences among parts. That means measurements are noisy and not dependable for making decisions about whether parts meet specifications or how processes are performing. In practical terms, you can’t trust who’s in spec or how the process is behaving because the gage is contributing more variability than the parts themselves. If the system were highly precise and repeatable, the gage’s contribution would be small, yielding a low percent gage R&R. If the measurement were perfectly unbiased, that would be about accuracy, not the amount of variability captured by gage R&R. Zero gage R&R would indicate an ideal measurement system with no added variability. The high percentage described here signals poor measurement reliability and the need to improve the gage, procedure, or operator training.

Gauge R&R shows how much of the total observed variation comes from the measurement system itself, by separating part-to-part variation from the noise introduced by the gage, including both repeatability and reproducibility. When the percent gage R&R is high, the measurement process is introducing a lot of variability relative to the actual differences among parts. That means measurements are noisy and not dependable for making decisions about whether parts meet specifications or how processes are performing. In practical terms, you can’t trust who’s in spec or how the process is behaving because the gage is contributing more variability than the parts themselves.

If the system were highly precise and repeatable, the gage’s contribution would be small, yielding a low percent gage R&R. If the measurement were perfectly unbiased, that would be about accuracy, not the amount of variability captured by gage R&R. Zero gage R&R would indicate an ideal measurement system with no added variability. The high percentage described here signals poor measurement reliability and the need to improve the gage, procedure, or operator training.