Exponential Weighted Moving Average Control Charts for Monitoring the Process Mean Using Pair Ranked Set Sampling Schemes

Abstract

An economical and efficient sampling scheme plays a vital role in the statistical process monitoring. In this paper, cost-efficient and precise pair ranked set sampling, extreme pair ranked set sampling (EPRSS) and recently suggested quartile pair ranked set sampling (QPRSS) schemes are exploited to propose new exponentially weighted moving average (EWMA) control charts, named EWMA-PRSS, EWMA-EPRSS and EWMA-QPRSS charts for efficiently monitoring the process mean. An extensive simulation study is carried out to compute run-length characteristics of the suggested control charts and compare with the simple random sampling (SRS)-based EWMA chart (EWMA-SRS). It is revealed that proposed EWMA-type charts, with either perfect or imperfect ranking, have better shift diagnostic abilities than the classical EWMA-SRS chart. This study also explored the in control robustness of the proposed charts under different non-normal distributions. An example of real data is also considered to demonstrate the working and implementation of the proposed EWMA-type control charts.