Control charts for monitoring the mean vector and the covariance matrix of bivariate processes.

Machado, Marcela; Costa, Antonio; Marins, Fernando

In this article, we propose new control charts for monitoring the mean vector and the covariance matrix of bivariate processes. The traditional tools used for this purpose are the T2 and the | S| charts. However, these charts have two drawbacks: (1) the T2 and the | S| statistics are not easy to compute, and (2) after a signal, they do not distinguish the variable affected by the assignable cause. As an alternative to (1), we propose the MVMAX chart, which only requires the computation of sample means and sample variances. As an alternative to (2), we propose the joint use of two charts based on the non-central chi-square statistic (NCS statistic), named as the NCS charts. Once the NCS charts signal, the user can immediately identify the out-of-control variable. In general, the synthetic MVMAX chart is faster than the NCS charts and the joint T2 and | S| charts in signaling processes disturbances.

ANALYSIS of covariance; GRAPHIC methods; QUALITY control charts; MATRICES (Mathematics); SYSTEMS engineering

International Journal of Advanced Manufacturing Technology, 2009, Vol 45, Issue 7/8, p772

0268-3768

Academic Journal

10.1007/s00170-009-2018-7