# Interpret the key results for Crossed Gage R&R Study

Complete the following steps to interpret a crossed gage R&R study. Key output includes variability estimates, and graphs of the measurements and measurement variability.

## Step 1: Use the ANOVA table to identify significant factors and interactions

Use the ANOVA table to identify which sources of variability are significant. The ANOVA table includes the following terms in the Source column:
• Part: The variation that is from the parts.
• Operator: The variation that is from the operators.
• Operator*Part: The variation that is from the operator and part interaction. An interaction exists when an operator measures different parts differently.
• Error or repeatability: The variation that is not explained by part, operator, or the operator and part interaction.
###### Note

If you select the Xbar and R option for Method of Analysis, Minitab does not display the ANOVA table.

If the p-value for the operator and part interaction is 0.05 or higher, Minitab removes the interaction because it is not significant and generates a second ANOVA table without the interaction.

## Step 2: Assess the variation for each source of measurement error

Use the variance components (VarComp) and %Contribution to assess the variation for each source of measurement error. The sources are as follows:
• Total Gage R&R: The sum of the repeatability and the reproducibility variance components.
• Repeatability: The variability in measurements when the same operator measures the same part multiple times.
• Reproducibility: The variability in measurements when different operators measure the same part.
• Part-to-Part: The variability in measurements due to different parts.

Ideally, very little of the variability should be due to repeatability and reproducibility. Differences between parts (Part-to-Part) should account for most of the variability.

## Step 3: Examine the graphs for more information on the gage study

The gage R&R graphs provide information about the measurement system.
Components of variation graph
Shows whether the largest of component of variation is part-to-part variation.
In an acceptable measurement system, the largest component of variation is part-to-part variation.
R chart by operator
Shows whether any points fall above the upper control limit.
If the operators measure consistently, the points will fall within the control limits.
Xbar chart by operator
Shows whether most points fall beyond the control limits.
The parts that you choose for a gage R&R study should represent the typical part-to-part variability. Thus, you should expect more variation between part averages, and the graph should show that most points fall beyond the control limits.
Measurements by part graph
Shows whether multiple measurements for each part are close together.
Multiple measurements for each part that are close together indicate small variation between the measurements of the same part.
Measurements by operator graph
Shows whether differences between operators are small compared to the differences between parts.
A straight horizontal line across operators indicates that the mean measurements for each operator are similar. Ideally, the measurements for each operator vary an equal amount.
The operator*part interaction graph
Shows whether the lines that connect the measurements from each operator are similar or whether the lines cross each other.
Lines that are coincident indicate that the operators measure similarly. Lines that are not parallel or that cross indicate that an operator's ability to measure a part consistently depends on which part is being measured. A line that is consistently higher or lower than the others indicates that an operator adds bias to the measurement by consistently measuring high or low.
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