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

Li-ping Liu (), Jian-lan Zhong and Yi-zhong Ma
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Li-ping Liu: Nanjing University of Science of Technology
Jian-lan Zhong: Nanjing University of Science of Technology
Yi-zhong Ma: Nanjing University of Science of Technology

Chapter Chapter 10 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 99-107 from Springer

Abstract: 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.

Keywords: Entropy; Multivariate control charts; Quality control; Statistical process control; Synthetic control chart (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-37270-4_10

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DOI: 10.1007/978-3-642-37270-4_10

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