# Overview for Evaluate Measurement Process (EMP Crossed)

Use Evaluate Measurement Process (EMP Crossed) to assess the variation in your measurement system when every operator measures every part in the study. To perform this study, you must have a balanced design with random factors.

For example, an engineer selects 10 parts that represent the expected range of the process variation. For the study, 3 operators measure the 10 parts, 3 times per part, in random order.

The results classify the measurement system from the best rating of first class to the worst rating of fourth class. The classes correspond to the intraclass correlation coefficient. 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.

Wheeler's Method and the Honest Gage R&R Study
Wheeler (2006) 1 describes the calculations, output, and classifications for the EMP crossed study. As such, the study is also known as Wheeler's Method. Within this book, the chapter title for the analysis uses the term Honest Gage R&R Study, which is another common name for the analysis.

## Where to find this analysis

To perform a crossed EMP study, choose Stat > Quality Tools > Gage Study > Evaluate Measurement Process (EMP Crossed).

## When to use an alternate analysis

The AIAG (2010)2 describes measurement system analyses with different ways to decide how well the systems work. To evaluate results that use AIAG methods, consider the following analyses.
1 Wheeler, D. J. (2006). EMP III: Evaluating the measurement process & using imperfect data. SPC Press, Knoxville, TN.
2 Automotive Industry Action Group (AIAG) (2010). Measurement Systems Analysis Reference Manual, 4th edition. Chrysler, Ford, General Motors Supplier Quality Requirements Task Force