We present an overview of the literature on nonparametric or distribution-free control charts
for univariate variables data. We highlight various advantages of these charts while pointing …

A major tool for quality control and management, statistical process control (SPC) monitors
sequential processes, such as production lines and Internet traffic, to ensure that they work …

Nonparametric control chart are presented for the problem of detecting changes in the
process median (or mean), or changes in the process variability when samples are taken at …

The assumption of fully known in-control distributions has long been recognized as an
idealization, at best approximately true. Recent development of normal-based change-point …

For effective monitoring of the range of sustainable changes in the process median, a
nonparametric adaptive cumulative sum signed‐rank (NPACUSUM‐SR) control chart has …

A unique approach to understanding the foundations of statistical quality control with a focus
on the latest developments in nonparametric control charting methodologies Statistical …

Since their inception by Walter Shewhart in the late 1920s, most control chart developments
have been distribution-based procedures in the sense that the process output is assumed to …

This article considers statistical process control (SPC) of univariate processes when the
parametric form of the process distribution is unavailable. Most existing SPC procedures are …

Traditional statistical process control for variables data often involves the use of a separate
mean and a standard deviation chart. Several proposals have been published recently …

Nonparametric control charts are useful when the underlying process distribution is not likely
to be normal or is unknown. In this paper, we propose two nonparametric analogs of the …