Is my measurement system acceptable?

The criteria for acceptability depends on the type of study.

In This Topic

Gage R&R criteria
Wheeler's EMP study criteria
How do the criteria differ?

Gage R&R criteria

According to AIAG¹ guidelines, if your measurement system's variation is less than 10% of process's variation, then it is acceptable. To evaluate your process variation, compare the Total Gage R&R contribution in the %StudyVar column (%Tolerance, %Process) in your output with the values in the table.

Percentage of process variation	Acceptability
Less than 10%	The measurement system is acceptable.
Between 10% and 30%	The measurement system is acceptable depending on the application, the cost of the measurement device, cost of repair, or other factors.
Greater than 30%	The measurement system is not acceptable and should be improved.

Guidelines using variance components

This table contains corresponding guidelines using variance components. To evaluate your variance components, compare the %Contribution column in your output with the values in the table.

Percentage of variance components	Acceptability
Less than 1%	The measurement system is acceptable.
Between 1% and 9%	The measurement system is acceptable depending on the application, the cost of the measurement device, cost of repair, or other factors.
Greater than 9%	The measurement system is not acceptable and should be improved.

Important

The AIAG also states that the number of distinct categories into which the measurement system divides process output should be greater than or equal to 5.

Wheeler's EMP study criteria

Guidelines for Wheeler's EMP study classify the measurement system into a class with the intraclass correlation coefficient. Wheeler (2006) ² describes the calculations, output, and classifications for the EMP crossed study. In practical terms, the coefficient explains how well the measurement system detects a shift in the process mean of at least 3 standard deviations. First and second class measurement systems usually have a high probability to detect such shifts with a limited number of tests and subgroups on a control chart. For third class measurement systems, the typical analysis adds tests to the control chart to increase the probability to detect a shift in the process mean. A fourth class measurement system usually requires improvement to monitor a process or for process improvement activities.

Classification Guidelines

Classification	Intraclass Correlation	Attenuation of Process Signals	Probability of Warning, Test 1*	Probability of Warning, Tests*
First Class	0.80 - 1.00	Less than 11%	0.99 - 1.00	1.00
Second Class	0.50 - 0.80	11 - 29%	0.88 - 0.99	1.00
Third Class	0.20 - 0.50	29 - 55%	0.40 - 0.88	0.92 - 1.00
Fourth Class	0.00 - 0.20	More than 55%	0.03 - 0.40	0.08 - 0.92

How do the criteria differ?

The two criteria lead to different conclusions. The classifications for Wheeler's EMP studies are less strict than the classifications for gage R&R studies that follow the AIAG methodology.

Table 1. Comparison of criteria. The table gives approximate values of the minimum intraclass correlation and the maximum percent of process variation where the criteria change classifications. With the AIAG criteria, a measurement system is most acceptable in the first row. With the EMP criteria, a measurement system is most acceptable in the first 3 rows.
Intraclass correlation	Percent of process variation	AIAG	EMP
99%	10%	Acceptable	First class
91%	30%	Marginal	First class
80%	45%	Needs improvement	First class
50%	71%	Needs improvement	Second class
20%	89%	Needs improvement	Third class
0%	100%	Needs improvement	Fourth class

The development of the AIAG criteria in the automotive industry is from a tradition of processes that require high precision from the measurements to meet tight tolerances. The development of the EMP criteria comes from a tradition that uses the measurement system to detect shifts in the process average for process improvement activities.

¹ Automotive Industry Action Group (AIAG) (2010). Measurement Systems Analysis Reference Manual, 4th edition. Chrysler, Ford, General Motors Supplier Quality Requirements Task Force

² Wheeler, D. J. (2006). EMP III: Evaluating the Measurement Process & Using Imperfect Data. SPC Press, Knoxville, TN.