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 out some of the disadvantages of the more traditional, distribution-based control charts. Specific observations are made in the course of review of articles and constructive criticism is offered so that opportunities for further research can be identified. Connections to some areas of active research are made, such as sequential analysis, that are relevant to process control. We hope that this article leads to a wider acceptance of distribution-free control charts among practitioners and serves as an impetus to future research and development in this area
Although the Shewhart chart is widely used in practice because of its simplicity, applying this cont...
Numerous nonparametric or distribution-free control charts have been proposed and studied in recent...
For the design of most multivariate control charts, it is assumed that the observations follow a mul...
We present an overview of the literature on nonparametric or distribution-free control charts for un...
An overview of the literature on some nonparametric or distribution-free quality control procedures ...
Control charts that are based on assumption(s) of a specific form for the underlying process distrib...
In general, statistical methods have two categories: parametric and nonparametric. Parametric analys...
Nonparametric or distribution-free charts can be useful in statistical process control problems when...
This paper deals with the methodology for practical application of nonparametric control charts. Thi...
Nonparametric or distribution-free charts can be useful in statistical process control when there is...
Control charts are widely used in statistical process control to detect changes in a production proc...
Autocorrelated data are common in today's process control applications. Many of these applications i...
<div><p>Monitoring multivariate quality variables or data streams remains an important and challengi...
A carefully done Phase I analysis is a vital part of an overall statistical process control and moni...
Standard control charts are often seriously in error when the distributional form of the observation...
Although the Shewhart chart is widely used in practice because of its simplicity, applying this cont...
Numerous nonparametric or distribution-free control charts have been proposed and studied in recent...
For the design of most multivariate control charts, it is assumed that the observations follow a mul...
We present an overview of the literature on nonparametric or distribution-free control charts for un...
An overview of the literature on some nonparametric or distribution-free quality control procedures ...
Control charts that are based on assumption(s) of a specific form for the underlying process distrib...
In general, statistical methods have two categories: parametric and nonparametric. Parametric analys...
Nonparametric or distribution-free charts can be useful in statistical process control problems when...
This paper deals with the methodology for practical application of nonparametric control charts. Thi...
Nonparametric or distribution-free charts can be useful in statistical process control when there is...
Control charts are widely used in statistical process control to detect changes in a production proc...
Autocorrelated data are common in today's process control applications. Many of these applications i...
<div><p>Monitoring multivariate quality variables or data streams remains an important and challengi...
A carefully done Phase I analysis is a vital part of an overall statistical process control and moni...
Standard control charts are often seriously in error when the distributional form of the observation...
Although the Shewhart chart is widely used in practice because of its simplicity, applying this cont...
Numerous nonparametric or distribution-free control charts have been proposed and studied in recent...
For the design of most multivariate control charts, it is assumed that the observations follow a mul...