The purpose of this paper is to provide an overview and our perspective of recent research
and applications of statistical process monitoring. The focus is on work done over the past …

Statistical quality control is a very useful tool in the hands of business in order to improve
their products quality. The control charts are the most widely used and the most effective tool …

In the world of business, quality improvement is of high importance for the manufacturing
industries. Statistical process control via control charts provides an online monitoring of the …

In this paper, sensor fault detection and isolation of time-varying nonlinear dynamical
systems is studied by utilizing an adaptive kernel principal component analysis (KPCA) …

Monitoring multivariate quality variables or data streams remains an important and
challenging problem in statistical process control (SPC). Although the multivariate SPC has …

Memory control chart such as multivariate CUSUM (MCUSUM) and multivariate EWMA
(MEWMA) control charts are considered superior for the detection of small-to-moderate …

The adaptive exponentially weighted moving average (AEWMA) control chart has the
advantage of detecting balance mixed range of mean shifts. Its performance has been …

An intermittent sampling model for statistical process control (SPC) is introduced to monitor
the quality of output from a production process where the number of defective units in a …

Multivariate process control in Distributed Sensor Networks (DSNs) is an important and
challenging topic. Although a fully deployed sensor network will minimize information loss …

In recent years, adaptive control charts in which the design parameters depend on the
observed samples have been successfully used as efficient alternatives for traditional …