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

- Operators should measure parts in a random order
- To ensure that the data collection order does not influence the results, each operator should measure all parts randomly within a replicate. After all operators measure all parts one time, you repeat the process for all replicates.
- Operators should measure at least 10 parts for an adequate study
- The process variation can be estimated from a large sample of historical data, or from the parts in the study. If you have a historical estimate of the process variation, the usual requirement of 10 parts is acceptable.
- 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.
- Operator and Part factors must be crossed
- Two factors are crossed when each level of one factor occurs in combination with each level of the other factor.
- Operator and Part factors must be random
- A factor is random when the factor has many possible levels, but only a random sample of the levels is included in the data.
- Operators must measure each part at least twice
- Measurement variation is broken down into two components: reproducibility and repeatability. Reproducibility is the variation that occurs when different people measure the same part. Repeatability is the variation that occurs when the same person measures the same part repeatedly. If you use at least 10 parts and at least 3 operators, having each operator measure each part at least 2 times, in random order, allows you to obtain an adequate estimate of repeatability.
- You should have at least 3 operators for an adequate study
- For the best results, include 3 to 5 operators in your study. You should not have fewer than 3 operators in the study, unless the number of operators who use the measurement system is actually less than 3. If you suspect that there are large differences between operators, you should consider using more than 3 to 5 operators. If you identify differences between operators, such as an operator whose measurements are lower than other operators, you can often improve consistency with training.