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2013 | OriginalPaper | Buchkapitel

10. A Multivariate Synthetic Control Chart for Monitoring Covariance Matrix Based on Conditional Entropy

verfasst von : Li-ping Liu, Jian-lan Zhong, Yi-zhong Ma

Erschienen in: The 19th International Conference on Industrial Engineering and Engineering Management

Verlag: Springer Berlin Heidelberg

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Abstract

In multivariate statistical process control field, besides monitoring the changes in the mean vector of a multivariate process, it is important to detect the changes in the covariance matrix of a multivariate process. This paper proposes a multivariate synthetic control chart for monitoring the changes in the covariance matrix of a multivariate process under multivariate normal distribution. The proposed control chart is a combination of the traditional control chart based on conditional entropy and the conforming run length chart. The operation and design of this control chart are described.

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Vorheriges Kapitel Multivariate Measurement System Analysis Based on Projection Pursuit Method

Nächstes Kapitel Multi-objective Robust Operation Model for a Supply Chain with Market Demands and Raw Material Price Uncertainty

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Titel: A Multivariate Synthetic Control Chart for Monitoring Covariance Matrix Based on Conditional Entropy
verfasst von: Li-ping Liu
Jian-lan Zhong
Yi-zhong Ma
Verlag: Springer Berlin Heidelberg
Buch: The 19th International Conference on Industrial Engineering and Engineering Management
Print ISBN: 978-3-642-37269-8

Electronic ISBN: 978-3-642-37270-4

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-3-642-37270-4_10