Multivariate control charts are essential tools in multivariate statistical process control. In real applications, when a multivariate process shifts, it occurs in either location or scale. Several methods have been proposed recently to monitor the covariance matrix. Most of these methods use rational subgroups and are used to detect large shifts. In this paper, we propose a new accumulative me...

The goal of engineering process control (EPC) is to minimize variability by adjusting some manipulative process variables. The goal of statistical process control (SPC) is to reduce variability by monitoring and eliminating assignable causes of variation. As suggested by Box and Kramer and others, it is possible to reduce both special cause and common cause variations by integrating EPC and SPC...

Multivariate control charts can be used effectively to monitor the quality of complex processes with several critical variables simultaneously. However, when the covariance matrix has large dimension in comparison to the number of runs available for parameter estimation, these charts can perform poorly. We incorporate prior information about the covariance matrix in which the number of paramete...

1 Corresponding author: [email protected]; 417-836-3119 ABSTRACT: Many different methods of synthesizing and analyzing environmental monitoring data exist. Given the diversity of current environmental monitoring projects, and the large number of scientists and policy-makers involved, there is a critical need for a universal format that both summarizes data sets and indicates any p...

In many circumstances, the quality of a process or product is best characterized by a given mathematical function between a response variable and one or more explanatory variables that is typically referred to as profile. There are some investigations to monitor autocorrelated linear and nonlinear profiles in recent years. In the present paper, we use the linear mixed models to account autocorr...

Multivariate statistical methods for the analysis, monitoring and diagnosis of process operating performance are becoming more important because of the availability of on-line process computers which routinely collect measurements on large numbers of process variables. Traditional univariate control charts have been extended to multivariate quality control situations using the Hotelling T2 stat...