Determination of the optimal allocation of parameters for gauge repeatability and reproducibility study

Abstract

Recently, gauge repeatability and reproducibility (GR&R) study has been highly regarded by the quality practitioners when QS9000 and D19000 become fashionable requirements for manufacturing industries. Measurement plays a significant role in helping organizations improve their product quality. Good quality of products is the key factor towards business success. Therefore, how to ensure the quality of measurement becomes an important task for quality practitioners. In performing the GR&R study, several parameters, such as the appropriate sample size of parts (n), number of inspectors (p) and replicate measurements (k) are frequently asked by quality personnel in industries. The adequacy of current way of (n, p, k) selection is very questionable. A statistical method using the shortest confidence interval and its associated computer programming algorithm are presented in this paper for evaluating the optimal allocation among sample size of parts (n), number of inspectors (p) and replicate measurements (k). Hopefully, it can provide a useful reference for quality practitioners in industries.

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 — 31 citations exist upstream.

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