In statistical quality control, an EWMA chart (or exponentially weighted moving average chart) is a type of control chart used to monitor either variables or attributes-type data using the monitored business or industrial process 's entire history of output. [1]

In the present article, we present an exponentiated exponentially weighted moving average (Exp-EWMA) control chart that weights the past observations of a process using an exponentiated function.

In this article, we develop a new control chart based on the Exponentially Weighted Moving Average (EWMA) statistic, termed the New Extended Exponentially Weighted Moving Average (NEEWMA) statistic, designed to recognize slight changes in the process mean.

Generate an Exponentially Weighted Moving Average (EWMA) chart based on the cycle time data, depicting the processing duration for customer orders in a car showroom over a specified period.

Unlike simple moving averages or Shewhart control charts that primarily detect large shifts, the EWMA chart is sensitive to smaller changes due to its unique weighting mechanism.

This research aimed to propose a newly-mixed control chart called the Exponentially Weighted Moving Average—Moving Average Chart (EWMA-MA) to detect the mean change in a process underlying symmetric and asymmetric distributions.

Consider the following data consisting of 20 points. These data represent control measurements from the process which is to be monitored using the EWMA control chart technique. The corresponding EWMA statistics that are computed from this data set are: The control chart is given below.

An exponentially weighted moving average (EWMA) is a filter of sequential process data, giving the most recent observation the most weight and older observations exponentially less weight. EWMA control charts are especially useful in detecting small shifts in the mean or variance of a process.

A numerical procedure using integral equations is presented for the tabulation of moments of run lengths of exponentially weighted moving average (EWMA) charts.

Like a cusum chart, an EWMA chart is an alternative to a Shewhart individuals or x chart and provides quicker responses to shifts in the process mean then either an individuals or x chart because it incorporates information from all previously collected data.