A one-sided MEWMA control chart for Poisson-distributed data

Busaba Laungrungrong; Connie M. Borror; Douglas Montgomery

doi:10.1504/IJDATS.2014.059013

A one-sided MEWMA control chart for Poisson-distributed data

Busaba Laungrungrong, Connie M. Borror, Douglas Montgomery

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

This paper introduces a one-sided multivariate exponentially weighted moving average (MEWMA) chart for detecting an increase in a process mean. The control limits are based on the multivariate Poisson distribution and have applications for both industrial processes and public health data. The statistical performance of the proposed MEWMA is examined using run length distributions and is also compared to the traditional MEWMA based on normal-theory limits. Two out-of-control scenarios are of interest: 1) detecting a single point plotting beyond the control limits 2) a run of two or more points in a row.

Original language	English (US)
Pages (from-to)	15-42
Number of pages	28
Journal	International Journal of Data Analysis Techniques and Strategies
Volume	6
Issue number	1
DOIs	https://doi.org/10.1504/IJDATS.2014.059013
State	Published - 2014

Keywords

Multivariate Poisson Distribution
One-Sided Mewma Control Chart

ASJC Scopus subject areas

Information Systems
Information Systems and Management
Applied Mathematics

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10.1504/IJDATS.2014.059013

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abstract = "This paper introduces a one-sided multivariate exponentially weighted moving average (MEWMA) chart for detecting an increase in a process mean. The control limits are based on the multivariate Poisson distribution and have applications for both industrial processes and public health data. The statistical performance of the proposed MEWMA is examined using run length distributions and is also compared to the traditional MEWMA based on normal-theory limits. Two out-of-control scenarios are of interest: 1) detecting a single point plotting beyond the control limits 2) a run of two or more points in a row.",

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AU - Montgomery, Douglas

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AB - This paper introduces a one-sided multivariate exponentially weighted moving average (MEWMA) chart for detecting an increase in a process mean. The control limits are based on the multivariate Poisson distribution and have applications for both industrial processes and public health data. The statistical performance of the proposed MEWMA is examined using run length distributions and is also compared to the traditional MEWMA based on normal-theory limits. Two out-of-control scenarios are of interest: 1) detecting a single point plotting beyond the control limits 2) a run of two or more points in a row.

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A one-sided MEWMA control chart for Poisson-distributed data

Abstract

Keywords

ASJC Scopus subject areas

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