Introduction:
Measurements are used to guide decisions, then it follows logically that the more error there is in the measurements, the more error there will be in the decisions based on those measurements.
Purpose
“The purpose of Measurement System Analysis is to qualify a measurement system for use by quantifying its accuracy, precision, and stability”.
Characterization: A measurement system can be characterized, or described, in five ways:
Location (Average Measurement Value vs. Actual Value):
1. Stability refers to the capacity of a measurement system to produce the same values over time when measuring the same sample. As with statistical process control charts, stability means the absence of "Special Cause Variation", leaving only "Common Cause Variation" (random variation).
2. Bias, also referred to as Accuracy, is a measure of the distance between the average value of the measurements and the "True" or "Actual" value of the sample or part. See the illustration below for further explanation.
3. Linearity is a measure of the consistency of Bias over the range of the measurement device. For example, if a bathroom scale is under by 1.0 pound when measuring a 150 pound person, but is off by 5.0 pounds when measuring a 200 pound person, the scale Bias is non-linear in the sense that the degree of Bias changes over the range of use.
Variation (Spread of Measurement Values - Precision):
Repeatability assesses whether the same appraiser can measure the same part/sample multiple times with the same measurement device and get the same value.
Reproducibility assesses whether different appraisers can measure the same part/sample with the same measurement device and get the same value.
The diagram below illustrates the difference between the terms "Accuracy" and "Precision": Efforts to improve measurement system quality are aimed at improving both accuracy and precision.