Robust X¯ Control Chart for Monitoring the Skewed and Contaminated Process

A Magnitude Robust Control Chart for Monitoring Process Dispersion

This paper introduces a new control chart for monitoring process dispersion that performs well regardless of the magnitude of the change. We compare the performance of this magnitude robust chart for dispersion (MRD) to that of others that appear in literature. While the MRD chart does not perform optimally at any specific magnitude of change in process dispersion, it performs nearly optimally ...

A Synthetic Scaled Weighted Variance Control Chart for Monitoring the Process Mean of Skewed Populations

In this paper, a synthetic scaled weighted variance Xbar (synthetic SWV-Xbar) control chart is proposed to monitor the process mean of skewed populations. A comparison between the performances of the synthetic SWV-Xbar and synthetic WV-Xbar charts are made in terms of the average run length (ARL) values for the various levels of skewnesses as well as different magnitudes of positive and negativ...

A Robust Control Chart for Monitoring Dispersion

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 disp...

A Control Chart for Monitoring Process Variability

The Shewhart and the Bonferroni-adjustment S control charts are usually applied to monitor the standard deviation of a quality characteristic. The control limits of these charts are constructed using approximately the normal distribution in case that the standard deviation parameter is known or unknown. In this paper, we establish a new S chart that is based approximately on the normal distribu...

Robust Holt-Winter based control chart for monitoring autocorrelated simple linear pro les with contaminated data