Control charts that are based on assumption (s) of a specific form for the underlying process
distribution are referred to as parametric control charts. There are many applications where …

A multivariate control chart is designed to monitor process parameters of multiple correlated
quality characteristics. Often data on multivariate processes are collected as individual …

In this paper, we develop two adaptive approaches for detecting the signal source in a
bivariate process when a shift occurs in the location vector or the scale matrix or both. The …

This paper offers new multivariate statistical process monitoring schemes to study the
process shift supported by a distinctive product quality features assessment. The proposed …

Parametric and nonparametric multivariate control charts that are proven very useful in
monitoring the covariance matrix of multivariate normally or “nearly” normally distributed …

This paper proposes an adaptive, multivariate, nonparametric, exponentially weighted
moving average control chart with variable sampling interval. A number of studies have …

Non-parametric control charts have been good alternatives to parametric control charts
when little information is known about the type of process distribution or the value of …

An efficient multivariate single control chart to simultaneously monitor 'location or mean'and
'scale or variabilities', based on individual observations of multiple quality characteristics …

Most existing control charts monitoring the covariance matrix of multiple variables were
restricted to multivariate normal distribution. When the process distribution is non-normal …

In multivariate statistical process control (MSPC) applications, process mean shifts
sometimes occur in only a few components. To solve this MSPC problem, many control …