A Multivariate Group Runs Control Chart for Process Dispersion

2013 ◽  
Vol 43 (4) ◽  
pp. 813-837 ◽  
Author(s):  
M. P. Gadre
Keyword(s):  
Control Chart ◽  
Process Dispersion

Comparing Robustness of EWMA Dispersion Control Chart for Non-Normal Process

2014 ◽  
Vol 912-914 ◽  
pp. 1189-1192
Author(s):  
Hai Yu Wang
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Normal Process ◽  
Comparison Analysis ◽  
Run Length ◽  
Monitoring Process ◽  
Process Dispersion

This article discusses robustness to non-normality of EWMA charts for dispersion. Comparison analysis of run length of four kinds of EWMA charts to monitoring process dispersion is provided to evaluate control charts performance and robustness. At last robust EWMA dispersion charts for non-normal processes are proposed by this way.

The SPRT Sign Chart for Process Dispersion

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Dadasaheb G. Godase ◽  
Shashibhushan B. Mahadik
Keyword(s):  
Control Chart ◽  
Sequential Probability Ratio Test ◽  
Ratio Test ◽  
Probability Ratio ◽  
Wide Range ◽  
Sequential Probability ◽  
Process Dispersion ◽  
Test Control

Abstract A nonparametric sequential probability ratio test control chart to monitor the process dispersion based on the sequential sign statistic is proposed. The statistical performance of this chart is evaluated by comparing it with that of the charts for dispersion based on sign statistic in the existing literature. It is found that the proposed chart outperforms all these charts uniformly in detecting a shift of any size over a wide range. An implementation of the chart is illustrated through an example.

scholarly journals A Robust Control Chart for Monitoring Dispersion

2013 ◽  
Vol 2013 ◽  
pp. 1-5
Author(s):  
Maoyuan Zhou ◽  
Wei Geng
Keyword(s):  
Robust Control ◽  
Control Chart ◽  
Control Charts ◽  
Nonparametric Test ◽  
Dispersion Parameters ◽  
Monitoring Process ◽  
Location Parameters ◽  
Process Dispersion ◽  
Change Point Model ◽  
Process Location

Most robust control charts in the literature are for monitoring process location parameters, such as mean or median, rather than process dispersion parameters. This paper develops a new robust control chart by integrating a two-sample nonparametric test into the effective change-point model. Our proposed chart is easy in computation, convenient to use, and very powerful in detecting process dispersion shifts.

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