Quality and Reliability Methods - SAS

Chapter 10 Variability Charts 163
R&R Measurement Systems
Figure 10.10 Analysis of Variance and Variance Components for Variability Analysis
R&R Measurement Systems
Measurement systems analysis is an important step in any quality control application. Before you study the
process itself, you need to make sure that you can accurately and precisely measure the process. This
generally means the variation due to measurement errors is small relative to the variation in the process. The
instruments that take the measurements are called gauges, and the analysis of their variation is a gauge study.
If most of the variation that you see comes from the measuring process itself, then you are not reliably
learning about the process. So, you do a measurement systems analysis, or gauge R&R study, to find out if
the measurement system itself is performing well enough.
Gauge R&R results are available for all combinations of crossed and nested models, regardless of whether
the model is balanced.
You collect a random sample of parts over the entire range of part sizes from your process. Select several
operators randomly to measure each part several times. The variation is then attributed to the following
sources:
• The process variation, from one part to another. This is the ultimate variation that you want to be
studying if your measurements are reliable.
• The variability inherent in making multiple measurements, that is, repeatability. In Table 10.2 on
page 163, this is called the within variation.
• The variability due to having different operators measure parts—that is, reproducibility.
A Gauge R&R analysis then reports the variation in terms of repeatability and reproducibility.
Table 10.2 Definition of Terms and Sums in Gauge R&R Analysis
Variances Sums Term Abbr. Alternate Term
V(Within) Repeatability EV Equipment Variation
V(Operator)+V(Operator*Part) Reproducibility AV Appraiser Variation