Abstract The Moving Average method is the most common filter in Digital Signal Processing, optimal for reducing unstable value fluctuations due to interference by maintaining accurate readings. Therefore it often used signal coding context of time (Smith, 1999). kind moving average Exponentially Weighted (EWMA) which applied a sequence random variables, calculating weighted applying weight that...

The mixed control chart is proposed to improve detection performance with fewer process shifts. In this study, we the modified exponentially weighted moving average - (MMEM), a new for observing changes in mean. Average run length, standard deviation of and median length can be used examine effectiveness detecting Shewhart, Moving (MA), Modified Exponentially Weighted (MEWMA), Mixed (MMME) char...

The reliability data is getting used to monitor and improve the quality of products or services. Nowadays, most of products or services are the results of processes with dependent stages referred to as multi-stage process. In these processes, the quality characteristics are affected by the quality characteristics in the previous stages, called as cascade property. In some cases, it is not possi...

Statistical process monitoring (SPM) literature recommends the combination of Shewhart and exponentially weighted moving average (EWMA) schemes to improve ability standalone EWMA in detecting small large shifts. The resulting scheme is named combined (or composite) Shewhart-EWMA (CSEWMA) scheme. In this paper, a new single composite (denoted as SCSEWMA) for mean when parameters are known or unk...

The Adaptive Exponentially Weighted Moving Average (AEWMA) control chart has the advantage of detecting in balance mixed range of mean shifts. Its performance has been studied under the assumption that the process parameters are known. Under this assumption, previous studies have shown that AEWMA provides superior statistical performance when compared to other different types of control charts....

Monitoring medical outcomes is desirable to help quickly detect performance changes. Previous applications have focused mostly on binary outcomes, such as 30-day mortality after surgery. However, in many applications the survival time data are routinely collected. In this paper, we propose an updating exponentially weighted moving average (EWMA) control chart to monitor risk-adjusted survival t...

A quality-control chart based on exponentially weighted moving averages (EWMA) has, in the past few years, become a popular tool for controlling inaccuracy in industrial quality control. In this paper, I explain the principles of this technique, present some numerical examples, and by computer simulation compare EWMA with other control charts currently used in clinical chemistry. The EWMA chart...

To detect sustainable changes in the manufacturing processes, memory-type charting schemes are frequently functioning. The recently designed, homogenously weighted moving average (HWMA) technique is effective for identifying substantial processes. make HWMA chart more persistent shifts industrial a double (DHWMA) has been proposed recently. This study intends to develop triple (THWMA) efficient...

Adaptive Cumulative SUM charts (ACUSUM) have been recently proposed for providing an overall good detection over a range of mean shift sizes. The basic idea of the ACUSUM chart is to first adaptively update the reference value based on an Exponentially Weighted Moving Average (EWMA) estimate and then to assign a weight on it using a certain type of weighting function. A linear weighting functio...