Abstract A single exponentially weighted moving average (EWMA) chart is effectively used for monitoring the process mean and variance simultaneously. In this paper, three single EWMA-type control charts including sum of square EWMA (SS-EWMA), maximum EWMA (MaxEWMA), and EWMA-semicircle (EWMA-SC) charts are compared under Lorenzen and Vance’s cost model integrating Taguchi’s loss function. The o...

Monitoring coefficient of variation is one of the successful approaches to Statistical Process Control (SPC) when the process mean and standard deviation are not constants. This paper presents a modified Exponentially Weighted Moving Average (EWMA) chart in order to further enhance the sensitivity of the EWMA control chart proposed by Castagliola et al. (2011). Tables are provided for the stati...

Quality control is an important role in industry for maintain quality stability. Statistical process can quickly investigate the occurrence of unforeseen causes or shifts using charts. Mixed Exponentially Weighted Moving Average - Cumulative Sum (MEC) chart a tool used to monitor and evaluate whether production not. The MEC method combination (EWMA) (CUSUM) Combining two charts aims increase se...

Distribution-free (nonparametric) control charts provide a robust alternative to a data analyst when there is lack of knowledge about the underlying distribution. A two-sided nonparametric Phase II exponentially weighted moving average (EWMA) control chart, based on the exceedance statistics (EWMA-EX), is proposed for detecting a shift in the location parameter of a continuous distribution. The...

Several forecast-based monitoring methods have been developed for autocorrelated data. One effective method is to use the forecasts based on the exponentially weighted moving average (EWMA). However, during the transition period of dynamic systems, the forecast-based monitoring procedure becomes inadequate due to its use of constant time series model parameters. In this article we present an ad...

The exponentially weighted moving average (EWMA) is a well-known and popular statistic used for smoothing and forecasting time series and as a process mean estimator, due to its simplicity and ability to capture nonstationarity. The EWMA statistic has been shown to be an optimal mean estimator for a certain disturbance process and an effective estimator for various other processes. In this arti...

In this paper we propose the explicit formulas of Average Run Length (ARL) of Exponentially Weighted Moving Average (EWMA) control chart for Autoregressive Integrated Moving Average: ARIMA (p,d,q) (P, D, Q)L process with exponential white noise. To check the accuracy, the ARL results were compared with numerical integral equations based on the Gauss-Legendre rule. There was an excellent agreeme...

The exponentially weighted moving average (EWMA) control chart became very popular during the last decade. It is characterized by simple handling and good performance. It turns out, however, that the most popular EWMA scheme with fixed-width control limits – the asymptotic control limits are taken and do not change over time – detects early changes rather slowly. For the competing CUSUM chart t...