Statistical process control plays a key role in today's highly competitive industrial
environment since it allows quality practitioners to timely detect out‐of‐control situations and …

In this paper, we propose an efficient control chart for monitoring small shifts in a process
mean for scenarios where the process variable is observed with a correlated auxiliary …

In today's competitive landscape, fulfilling customer expectations and achieving a
competitive edge are crucial for business success. These objectives can be attained by …

The performance of control charts can be adversely affected when based on parameter
estimates instead of known in‐control parameters. Several studies have shown that a large …

This paper can be considered as an extension of the work of Tran et al (for monitoring
compositional data using a multivariate exponentially weighted moving average MEWMA …

This paper presents a multivariate homogeneously weighted moving average (MHWMA)
control chart for monitoring a process mean vector. The MHWMA control chart statistic gives …

The SARS COVID-19 pandemic highlighted the importance of routine indoor air quality (IAQ)
monitoring. Recent advances in IAQ sensors and remote logging technologies offer …

Process monitoring through control charts is a quite popular practice in statistical process
control. From a statistical point of view, a superior control chart is the one which has an …

Recently, the monitoring of compositional data by means of control charts has been
investigated in the statistical process control literature. In this article, we develop a Phase II …

The adaptive exponentially weighted moving average (AEWMA) control chart has the
advantage of detecting balance mixed range of mean shifts. Its performance has been …