Gauge R&R analysis is based on a type of ANOVA model called a Random Effects model, also known as a Variance Components model.
The standard GR&R model supposes that each specimen or part can be tested or measured multiple times without changing the characteristic being measured and without destroying the part. If this is not the case, then a Destructive GR&R (DGR&R) model might be considered.
Standard GR&R models might be fit using either the Range method or the ANOVA method. The ANOVA method will often provide more information for the same amount of effort; such as determining if any interactions (e.g. Operator x Part, Operator x Gauge) are significant. The ANOVA method also allows model diagnostics, such as analysis of model residuals.
The ANOVA method used for GR&R is the Random Effects ANOVA model (vs. the Fixed Effects ANOVA model). See the Montgomery SQC text, among others.
Planning the study.
See notes on randomization and collection of specimens. (3 stage process)
What goes into the report? (see report template for ANOVA)
Study design
Sampling and randomization plan
GR&R Results
Random Effects ANOVA analysis
get GR&R variance components AND interaction(s)
can include any blocking term related to restrictions on randomization (as fixed effect)
Values for Repeatability and Reproducibility
Total GR&R as a percent of process variation
Prefer "as percent of process variation", for example if using results of measurements for SPC
Depending on application, might accept "percent of Tolerance"
Number of Distinct Categories (or equivalent)
Depending on risk, also consider calculating the confidence intervals around each GR&R component.
Model diagnostics
Check the computer generated EMS table against the manually created EMS table
Check the allocation of degrees of freedom
Check the denominator synthesis
Residuals -> homogeneity, iid N(0.1))
Supplementary analysis
Impact of any blocking variables
Fixed Effects ANOVA analysis of GR&R study data to explore:
Differences in means between levels of factors (operators, gauges, facilities, etc.)
Associated means plots (prioritize interaction terms)
Levene's test (or equivalent) to check for differences in variances between levels of factors
Plot of means vs. variances (prioritize interaction terms)
Blocking variables
Cavity
Test sequence ID
Position
12, 3, 6, 9 clock positions
Position across a web of film or barrier perform
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