APPLYING PRINCIPAL COMPONENT ANALYSIS TO A GR&R STUDY

Abstract

The gauge repeatability and reproducibility (GR&R) study is typically conducted on a single quality characteristic. However, manufacturing tests in a GR&R study usually have multiple characteristics with a multivariate normal distribution. Principal component analysis (PCA) method can transform the multiple characteristics into one or a few irrelevant variables and provide sufficient information. Then, these irrelevant variables were analyzed using analysis of variance. Two composite indices such as precision to tolerance (P/T) ratio and measurement variation to total variation of measurement system ratio (σ2 gauge /σ2 Total ) combining from all variables were used to evaluate the adequacy for the measurement process. A real example was used to demonstrate the application of the proposed methodology.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 20 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.