Glossary

Measurement system analysis (Gauge R&R)

Definition

Measurement system analysis (MSA) determines how much of the observed variability is caused by the measurement itself. A repeatability and reproducibility study (Gauge R&R) splits variability into parts, instrument (repeatability) and operators (reproducibility). A measurement system is acceptable when its share of total variability or tolerance stays around 10 %; up to 30 % is conditionally usable.

Quality control & SPC

Without a verified measurement neither control charts nor capability indices make sense — they may describe gauge noise instead of the process. A typical study: 10 parts × 3 operators × 2–3 repeats, evaluated by the average-and-range method or ANOVA, which can reveal the operator × part interaction.

For attribute inspection (pass/fail) an appraiser agreement study (kappa) is used. Gauge linearity and stability over time are assessed as well. Results are expressed as %R&R relative to tolerance and the number of distinct categories (ndc ≥ 5).

In Statistica

Statistics → Industrial Statistics & Six Sigma → Process Analysis contains Gauge R&R by the range and ANOVA methods, linearity and stability studies, attribute MSA (kappa) and plots of variance components, operator × part interactions and R charts by operator; it generates the study design together with a data-collection sheet.

Related terms

Knowledgebase guides

FAQ

What %R&R is acceptable?
Up to 10 % acceptable, 10–30 % conditionally depending on cost and importance of the characteristic, above 30 % unacceptable — improve the gauge before further decisions.
Range method or ANOVA?
ANOVA is more precise and reveals the operator × part interaction; the average-and-range method is simpler and still common in the automotive industry (AIAG).

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