To determine if a measurement system can generate accurate data, and if the accuracy is adequate to achieve your objectives
To make sure that the differences in the data are due to actual differences in what is being measured and not to variation in measurement
| Note |
Experience shows that 30% to 50% of measurement systems are not capable of accurately or precisely measuring the desired metric |
Gage R&R (
Bias Analysis ( see p. 95)
Stability Analysis ( see p. 97)
Discrimination Analysis ( see p. 99)
Kappa Analysis ( see p.100)
Measurements need to be "precise" and "accurate." Accuracy and precision are different, independent properties:
Data may be accurate (reflect the true values of the property) but not precise (measurement units do not have enough discriminatory power)
Vice versa, data can be precise yet inaccurate (they are precisely measuring something that does not reflect the true values)
Sometimes data can be
Obviously, the goal is to have data that are both precise and accurate
From a statistical viewpoint, there are four desirable characteristics that relate to precision and accuracy of continuous data:
No systematic differences between the measurement values we get and the "true value" (lack of bias, see p. 95)
The ability to get the same result if we take the same measurement repeatedly or if different people take the same measurement ( Gage R&R, see p. 87)
The ability of the system to produce the same results in the future that it did in the past ( stability, see p. 97)
The ability of the system to detect meaningful differences (good discrimination, see p. 99)
(Another desirable characteristic,
| Note |
Having uncalibrated measurement devices can affect all of these factors. Calibration is not covered in this book since it varies considerably depending on the device. Be sure to follow established procedures to calibrate any devices used in data collection. |
Gage R&R involves evaluating the
reliability
and
Repeatability refers to the inherent variability of the measurement system. It is the variation that occurs when successive measurements are made under the same conditions:
Same person
Same thing being measured
Same characteristic
Same instrument
Same
Same environmental conditions
Reproducibility is the variation in the average of the measurements made by different operators using the same measuring instrument and technique when measuring the identical characteristic on the same part or same process.
Different person
Same part
Same characteristic
Same instrument
Same setup
Same environmental conditions
Identify the elements of your measurement system (equipment, operators or data collectors,
Check that any measuring instruments have a discrimination that is equal to or less than 1/10 of the expected process variation/specification range
Select the items to include in the Gage R&R test. Be sure to represent the entire range of process variation. (Good and Bad over the entire specification plus slightly out of spec on both the high and low sides).
Select 2 or 3 operators to participate in the study.
Identify 5 to 10 items to be measured.
Make sure the items are
Have each operator measure each item 2 to 3 times in random sequence.
Gather data and analyze. See pp. 90 to 95 for interpretation of typical plots generated by statistical software.
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