Improved quality control charts for monitoring the process mean, using double-ranked set sampling methods

TLDR

Statistical control charts are widely used in manufacturing to monitor process quality. This study develops Shewhart‑type control charts that improve process‑mean monitoring by employing double quartile‑ranked, quartile double‑ranked, and double extreme‑ranked set sampling methods. The authors compare the average run length of the proposed charts with those based on simple random sampling, ranked set sampling, and extreme‑ranked set sampling, and evaluate performance using real data. Results show that the new control charts outperform existing counterparts.

Abstract

Statistical control charts are widely used in the manufacturing industry. The Shewhart-type control charts are developed to improve the monitoring process mean by using the double quartile-ranked set sampling, quartile double-ranked set sampling, and double extreme-ranked set sampling methods. In terms of the average run length, the performance of the proposed control charts are compared with the existing control charts based on simple random sampling, ranked set sampling and extreme-ranked set sampling methods. An application of real data is also considered to investigate the performance of the suggested process mean control charts. The findings of the study revealed that the newly suggested control charts are superior to the existing counterparts.