This paper concerns the design and analysis of the standard deviation control chart with
estimated limits. We consider an extensive range of statistics to estimate the in-control …

Statistical methods enable rational and quantitative studies of systems or processes, and
support management decisions. Statistical Process Control (SPC) is a standard …

Monitoring the multivariate coefficient of variation over time is a natural choice when the
focus is on stabilising the relative variability of a multivariate process, as is the case in a …

When the experimental data set is contaminated, we usually employ robust alternatives to
common location and scale estimators such as the sample median and Hodges-Lehmann …

Cumulative sum (CUSUM) control charts are very effective in detecting special causes. In
general, the underlying distribution is supposed to be normal. In designing a CUSUM chart …

Process monitoring through control charts is a quite popular practice in statistical process
control. From a statistical point of view, a superior control chart is the one which has an …

This article studies estimation methods for the location parameter. We consider several
robust location estimators as well as several estimation methods based on a phase I …

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

In many manufacturing industries, quality of an item depends on different characteristics and
their relationship may be modeled by profiles. For instance, in photo-voltaic (PV) system …

Control charts play a crucial role in industry, facilitating retrospective analysis of process
data during its initial phase (Phase I) and monitoring its behavior over time once a chart is …