The Gage R&R output shows how the total variability is divided up among the following sources:

·    Total Gage R&R, which can be broken into

·    Repeatability, which is the variability in measurements obtained when parts from the same batch are measured multiple times by the same operator

·    Reproducibility, which is the variability in measurements obtained when parts are measured by different operators.

·    Part-To-Part, which is the variability in measurements across different parts.

Ideally, very little of the variability should be due to repeatability and reproducibility; instead, differences between parts (Part-to-Part) should account for most of the variability. This would be shown by:

·    A small %Contribution for the sources Repeatability and Reproducibility.

·    A large %Contribution for the source Part-to-Part.

The most important information is found in the %Contribution, %Study Var, %Tolerance, and %Process columns. These columns show the sources of variation. Typically, the Total Gage R&R should equal less than 30% of the study variation, and less than 10% would be ideal.

If you entered a process tolerance or a historical standard deviation, then either the %Tolerance or the %Process column may be more important than %Study Var.

For the temperature data, the Total Gage R&R equals 92.91% of the study variation. This means that almost all of the variability in the temperature measurements is due to either the gage or the operators. It appears as if some corrective action should be taken. This action may include training of operators or acquiring better gages.