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 and exponentially weighted moving average are also named as memory-
type statistical process control charts for they are good at quickly detecting the presence of …

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 …

Control charts are powerful tools to observe the presentation of the manufacturing process.
Mostly, when the data in industries come from the process may follow non-normal or …

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 …

EWMA and Max-EWMA charts are considered efficient for individual as well as joint
monitoring of mean and variance shifts in the production process. However, measurement …

The memory control charts, including cumulative sum (CUSUM) and exponentially weighted
moving average (EWMA) control charts, are widely used to monitor small‐to‐moderate shifts …

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) …

In this paper, we have proposed a new modified Exponentially Weighted Moving Average
location control chart named as a modified-mxEWMA chart. The newly proposed chart uses …

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 …