We review the rapidly growing literature on auxiliary information-based (AIB) process
monitoring methods. Under this approach, there is an assumption that the auxiliary variable …

Cumulative sum (CUSUM) and exponentially weighted moving (EWMA) control charts,
known as memory control charts, are famous to monitor a small-to-moderate shift in the …

A control chart is an important statistical tool for monitoring disturbances in a statistical
process, and it is richly applied in the industrial sector, the health sector and the agricultural …

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

When using control charts to monitor manufacturing processes, Shewhart control chart is
known to be useful for detecting transient shifts, while the EWMA and CUSUM charts are …

Exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts are
used to detect smaller shifts in process parameters. The usual EWMA and CUSUM charts …

Control charts are popular monitoring tools in statistical process control toolkit. These are
used to identify assignable causes in the process parameters (location and/or dispersion) …

The CUSUM chart is good enough to detect small-to-moderate shifts in the process
parameter (s) as it can be optimally designed to detect a particular shift size. The adaptive …

Variation is an important phenomenon of the output of every manufacturing and production
process. To deal with the natural and special cause variations in the process, quality …

In this study, a new idea has been proposed in statistical process control by making dual use
of auxiliary information, that is, for ranking as well as at the estimation stage. The control …