The Design of the Multivariate Synthetic Exponentially Weighted Moving Average Control Chart

• Published in: Communications in statistics. Simulation and computation Vol. 41; no. 10; pp. 1785 - 1793
• Main Author: Lee, Ming Ha
• Format: Journal Article
• Language: English
• Published: Colchester Taylor & Francis Group 01-11-2012; Taylor & Francis; Taylor & Francis Ltd
• Subjects: Applications; Average run length; Combinatorics; Combinatorics. Ordered structures; Control charts; Designs and configurations; Exact sciences and technology; Experimental design; Markov analysis; Markov chain approach; Mathematics; Multivariate exponentially weighted moving average chart; Numerical analysis; Numerical analysis. Scientific computation; Numerical methods in probability and statistics; Probability and statistics; Reliability, life testing, quality control; Sciences and techniques of general use; Statistics; Studies; Synthetic chart; 62P30; Control chart; Moving average; Average run length; Synthetic chart; Multivariate analysis; Stochastic method; Mean estimation; Markov chain approach; Markov chain; Industry; Statistical method; Engineering; Experimental design; Numerical simulation; Multivariate exponentially weighted moving average chart; 62H86
• ISSN: 0361-0918; 1532-4141
• DOI: 10.1080/03610918.2011.620205

A multivariate synthetic exponentially weighted moving average (MSEWMA) control chart is presented in this study. The MSEWMA control chart consists of a multivariate exponentially weighted moving average (MEWMA) control chart and a conforming run length control chart. The average run length of the MSEWMA control chart is obtained using a Markov chain approach. From the numerical comparisons, it is shown that the MSEWMA control chart is more efficient than the multivariate synthetic T
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control chart and the MEWMA control chart for detecting shifts in the process mean vector.