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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Acknowledgment
This work is supported by the National Natural Science Foundation of China (NSFC) under grant No. 70931002 and China Postdoctoral Science Foundation under grant No. 2011 M500928.
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Liu, Lp., Zhong, Jl., Ma, Yz. (2013). A Multivariate Synthetic Control Chart for Monitoring Covariance Matrix Based on Conditional Entropy. In: Qi, E., Shen, J., Dou, R. (eds) The 19th International Conference on Industrial Engineering and Engineering Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37270-4_10
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DOI: https://doi.org/10.1007/978-3-642-37270-4_10
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