Measurement error is unavoidable. There will always be some measurement variation that is due to the measurement system itself.
Most
problematic measurement system issues come from measuring attribute
data in terms that rely on human judgment such as good/bad, pass/fail,
etc. This is because it is very difficult for all testers to apply the
same operational definition of what is “good” and what is “bad.”
However,
such measurement systems are seen throughout industries. One example is
quality control inspectors using a high-powered microscope to determine
whether a pair of contact lens is defect free. Hence, it is important
to quantify how well such measurement systems are working.
The
tool used for this kind of analysis is called attribute gage R&R.
The R&R stands for repeatability and reproducibility. Repeatability
means that the same operator, measuring the same thing, using the same
gage, should get the same reading every time. Reproducibility means that
different operators, measuring the same thing, using the same gage,
should get the same reading every time.
Attribute
gage R&R reveals two important findings – percentage of
repeatability and percentage of reproducibility. Ideally, both
percentages should be 100 percent, but generally, the rule of thumb is
anything above 90 percent is quite adequate.
Obtaining
these percentages can be done using simple mathematics, and there is
really no need for sophisticated software. Nevertheless, Minitab has a
module called Attribute Agreement Analysis (in Minitab 13, it was called
Attribute Gage R&R) that does the same and much more, and this
makes analysts’ lives easier.
Having
said that, it is important for analysts to understand what the
statistical software is doing to make good sense of the report. In this
article, the steps are reproduced using spreadsheet software with a case
study as an example