A multivariate synthetic control chart for monitoring covariance matrix based on conditional entropy

7Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.
Get full text

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. © 2013 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Liu, L. P., Zhong, J. L., & Ma, Y. Z. (2013). A multivariate synthetic control chart for monitoring covariance matrix based on conditional entropy. In 19th International Conference on Industrial Engineering and Engineering Management (pp. 99–107). https://doi.org/10.1007/978-3-642-37270-4_10

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free