A free online reference for statistical process control, process capability analysis, measurement systems analysis, control chart interpretation, and other quality metrics.

# How do you interpret an R&R study?

After performing an R&R study, which can be done using software such as GAGEpack, there are a number of ways to interpret the results. Frequently, since R&R is done in response to a customer requirement, the customer will indicate how to interpret the results. The most common here is the AIAG (Automotive Industry Action Group) standards, which are based on the R&R percentage given under study results. These results may be calculated as a percent of study variation, percent of specification, or percent of process variation.

For percent of study, the process variation is based on the spread of the parts (P) determined by . This is considered a range and using the /d2 relationship, a sigma for the process is estimated. This is then used to calculate the percentages.

A second method is to use the spread of the specs (USL - LSL). Now this must be compared to the estimate of the measurement error (R&R). However, one needs to multiply the sigma of the measurement by 5.15 (old method) or by 6.0 (new method) to compare the total measurement spread with the spec spread. (An alternative method is to divide the spec range by the respective numbers given above.)

The third method uses the information from an chart on the process and characteristic being studied. In this case, enter the , the , and the sample size. This is used to estimate the process spread.

Ideally the measurement error (R&R%) is less than 10% of whatever method is used (process spread or spec spread). It is usable in some cases when the R&R percentage is between 10 and 30%. More than 30% suggests that one should not be using it. [page 60 of MSA Manual 2nd edition or page 77 of MSA Manual 3rd edition]

If the number of distinct categories is 5 or more, it can be considered a capable measurement system. Wheeler and Lyday use a concept closely aligned with distinct categories called discrimination ratio, for which greater than four is satisfactory. The differences, in a nutshell, are that the distinct categories is a truncated number (no rounding or fraction used) and the discrimination Ratio assumes that appraiser variation has been reduced to zero and carries the fractional part as well.