In this paper we discuss the basic procedures for the implementation of multivariate
statistical process control via control charting. Furthermore, we review multivariate …

In this paper, we review multivariate control charts designed for monitoring changes in a
covariance matrix that have been developed in the last 15 years. The focus is on control …

This paper considers Statistical Process Control (SPC) when the process measurement is
multivariate. In the literature, most existing multivariate SPC procedures assume that the in …

This paper proposes a wavelet-based statistical signal detection approach for monitoring
and diagnosis of bearing compound faults at an early stage. The bearing vibration signal is …

Most of the existing control charts for monitoring multivariate process variability are based on
subgroup sizes greater than one. In many practical applications, however, only individual …

Multivariate control charts are considered for the simultaneous monitoring of the mean
vector and covariance matrix when the joint distribution of process variables is multivariate …

Adaptive EWMA (AEWMA) control charts have gained remarkable recognition by monitoring
productions over a wide range of shifts. The adaptation of computational statistic as per …

Recently, monitoring the process mean and variability simultaneously for multivariate
processes by using a single control chart has drawn some attention. However, due to the …

Papers on the analysis of means (ANOM) have been circulating in the quality control
literature for decades, routinely describing it as a statistical stand-alone concept. Therefore …

A control chart is proposed to effectively monitor changes in the population variance-
covariance matrix of a multivariate normal process when individual observations are …