Data considerations for Nested Gage R&R Study

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

Data should be collected in a random order
Because parts are nested in operators, the data cannot be completely randomized. However, to randomize the data as much as possible, randomly select the operators, randomly select the parts, and instruct the operators to measure their parts in random order.
Select parts that represent the actual or expected range of process variation
Select parts from the entire range of your process to increase the likelihood of having a good estimate of the part-to-part variation. For example, do not measure consecutive parts, parts from a single shift or a single production line, or parts from the reject pile.
Part is nested in Operator
Two factors are nested when each level of one factor occurs with only one level of the other factor. For example, if two operators measure two different, but similar, sets of parts, parts are nested under operator, and is indicated by Part (Operator).
For more information on nested factors, go to Types of factors in gage R&R studies and Wheeler's EMP studies.
Operator and Part must be random
A factor is random when it has many possible levels, but only a random sample of the levels is included in the data.
For example, Part is a random factor because the parts selected for the study represent all possible parts from the process.
For more information on random factors, go to Types of factors in gage R&R studies and Wheeler's EMP studies.