Nonparametric control charts are more practical tools for statistical process control (SPC), as
they are robust in situations in which the underlying distribution is unknown …

Control charts that are typically based on the assumption of a specific form of a parametric
distribution, such as the normal, are called parametric control charts. In many applications …

Investigation and removal of unnatural variation in the processes of manufacturing,
production and services require application of statistical process control. Control charts are …

In this chapter, we provide an up-to-date overview of nonparametric Shewhart-type
univariate control charts. The monitoring schemes incorporated in the present literature …

High-dimensional data, characterized by having more attributes or variables than
observations, presents unique challenges in industrial operations surveillance. Traditional …

The nonparametric (NP) control charts are famous for detecting a shift in the process
parameters (location and/or dispersion) when the underlying process characteristic does not …

In many quality control applications, the necessary distributional assumptions to correctly
apply the traditional parametric control charts are either not met or there is simply no enough …

In this paper, a new distribution-free double exponentially weighted moving average
(DEWMA) control chart based on the Wilcoxon rank-sum (WRS) test without any …

In the present paper we provide an up-to-date overview of nonparametric Cumulative Sum
(CUSUM) monitoring schemes. Due to their nonparametric nature, such memory-type …

In this article, we introduce new nonparametric Shewhart-type control charts that take into
account the location of two order statistics of the test sample as well as the number of …