Browsing by Author "Abbasi, Saddam Akber"
Now showing items 1-6 of 6
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Efficient GLM-based control charts for Poisson processes
( John Wiley & Sons, Ltd , 2022 , Article)The control charts are essential instruments that can impart crucial insights to quality controllers for maintaining the productivity of manufacturing processes. The conventional charting designs are based on a single study ... -
An Efficient Robust Nonparametric Triple EWMA Wilcoxon Signed-Rank Control Chart for Process Location
( Hindawi , 2021 , Article)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 follow the distributional assumptions. ... -
Enhancing the detection ability of control charts in profile monitoring by adding RBF ensemble model
( Springer , 2022 , Article)While numerous contributions and applications have been extended in profile monitoring, little attention has been paid to employing machine learning techniques in development of control charts. In this paper, a novel control ... -
Exponentially weighted moving average control charts for monitoring coefficient of variation under ranked set-sampling schemes
( Taylor and Francis , 2021 , Article)Several coefficients of variation (CV) control charts under simple random schemes (SRS) have been proposed to monitor process relative variability. However, little attention has been given to investigating the performance ... -
Multivariate control charts for monitoring process mean vector of individual observations under regularized covariance estimation
(2021 , Article)Multivariate control charts are generally used in industries for monitoring and diagnosing processes characterized by several process variables. The applications of charts assume that the in-control process parameters are ... -
Nonparametric multivariate covariance chart for monitoring individual observations
( Elsevier , 2022 , Article)Parametric and nonparametric multivariate control charts that are proven very useful in monitoring the covariance matrix of multivariate normally or “nearly” normally distributed continuous datasets have been proposed in ...
