A multivariate triple exponentially weighted moving average control chart

Abstract

Statistical process monitoring (SPM) is mostly populated with univariate control charts used to monitor a single variable (or quality characteristic). Nowadays, industries and online environments are filled with processes in which two or more quality characteristics are related. In such situations, univariate control charts are replaced with multivariate control charts for the sake of monitoring several characteristics simultaneously. This paper develops a new multivariate triple exponentially weighted moving average (MTEWMA) chart to serve this purpose. Moreover, the design of the multivariate simple and double exponentially weighted moving average (denoted as MEWMA and MDEWMA) charts are revisited using extensive simulations. It is observed that the MTEWMA chart has very interesting time‐varying properties as compared to the asymptotic properties. The newly proposed MTEWMA chart is superior over the MEWMA and MDEWMA charts in many situations of the asymptotic control limits. An illustrative example is provided to demonstrate the sensitivity of the proposed charts.

Comprehensive Scientometric Analysis and Longitudinal SDG Mapping of Quality and Reliability Engineering International Journal

“…Based on APY, the most recent topic from the cluster is "triple exponentially weighted moving average", with an APY score of 2021.3. Abbas et al [53] and Machado et al [54] feature as the top-cited articles on weighted moving average and synthetic control chart in our list cited 138 and 43 times, respectively, while Malela-Majika et al [55] article is the most recent on triple exponentially weighted moving average control chart in our list.…”