Gage repeatability and reproducibility study (Gage R&R Study)

A Measurement System Analysis (MSA) method which evaluates your measurement system precision and estimates the combined measurement system repeatability and reproducibility. A Gage R&R Study helps you answer whether your measurement system variability is small compared with the process variability, how much variability in the measurement system is caused by differences between operators, and whether your measurement system is capable of discriminating between different parts.

For example, several inspectors measure the diameter of screws to make sure they meet specifications. You want to make sure you trust your data so you examine whether the inspectors are consistent in their measurements of the same part (repeatability) and whether the variation between inspectors is consistent (reproducibility).

Although the number of inspectors, parts, and trials will change for your particular application, a general procedure follows:

1    Collect a sample of 15 screws that represent the entire range of your process.

2    Randomly choose 3 inspectors from the regular operators of this process (they should be trained and familiar with the process because you are trying to estimate the actual process, not the best or worst case).

3    It is best to randomize the order of the measurements, but sometimes this is not always possible. An alternative could be to randomize the order of the operators then have each one measure all 15 screws in random order. Record the data in a Minitab worksheet.

4    Repeat step 3 for the second trial.

When all the trials have been completed, Minitab can analyze your data. According to the Automobile Industry Action Group (AIAG) you can determine whether your measurement system is acceptable using the following guidelines.

If the Total Gage R&R contribution in the %Study Var column (% Tolerance, %Process) is:

·    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 measuring device, cost of repair, or other factors.

·    Greater than 30% - the measurement system is unacceptable and should be improved.