A single statistic for monitoring the covariance matrix of bivariate processes

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Data

2012-01-01

Autores

Quinino, Roberto
Costa, A. [UNESP]
Ho, Linda Lee

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Editor

Taylor & Francis Inc

Resumo

In this article, we present a new control chart for monitoring the covariance matrix in a bivariate process. In this method, n observations of the two variables were considered as if they came from a single variable (as a sample of 2n observations), and a sample variance was calculated. This statistic was used to build a new control chart specifically as a VMIX chart. The performance of the new control chart was compared with its main competitors: the generalized sampled variance chart, the likelihood ratio test, Nagao's test, probability integral transformation (v(t)), and the recently proposed VMAX chart. Among these statistics, only the VMAX chart was competitive with the VMIX chart. For shifts in both variances, the VMIX chart outperformed VMAX; however, VMAX showed better performance for large shifts (higher than 10%) in one variance.

Descrição

Palavras-chave

Bivariate processes, Control chart, Variance monitoring

Como citar

Quality Engineering. Philadelphia: Taylor & Francis Inc, v. 24, n. 3, p. 423-430, 2012.