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...

The Multivariate EWMA control chart, MEWMA, Lowry, Woodall, Champ and Ridgon [1] and its univariate version EWMA, may be designed to efficiently detect small shifts in the mean vector of a set of p quality characteristics of a production process. However, this work presents a method for the optimal design of MEWMA and EWMA charts parameters to control processes where it is not convenient to det...

The exponentially weighted moving average (EWMA) X chart is effective in detecting small shifts. However, the EWMA X chart is not robust enough to prevent errors in estimating the process standard deviation or a changing standard deviation. To overcome this problem, Zhang et al. suggested the EWMA t chart in 2009. The existing optimal design of the EWMA t chart is based on the average run lengt...

Shewhart, exponentially weighted moving average (EWMA), and cumulative sum (CUSUM) charts are famous statistical tools, to handle special causes and to bring the process back in statistical control. Shewhart charts are useful to detect large shifts, whereas EWMA and CUSUM are more sensitive for small to moderate shifts. In this study, we propose a new control chart, named mixed CUSUM-EWMA chart...

A one-sided Exponential Weighted Moving Average (EWMA) control chart is introduced to monitor the fraction p of nonconforming products in high yield processes. It is designed to detect upward shifts of p screening the non-transformed geometric counts i.e. the number of conforming products between two nonconforming ones. Its algorithmic function is theoretically established and numerous performa...

Generally, the traditional Shewhart p chart has been developed by for charting the binomial data. This chart has been developed using the normal approximation with condition as low defect level and the small to moderate sample size. In real applications, however, are away from these assumptions due to skewness in the exact distribution. In this paper, a modified Exponentially Weighted Moving Av...

The multi-chart consists of several CUSUM or EWMA charts with different reference values that are used simultaneously to detect anticipated process changes. We not only prove that the chart can quickly achieve the asymptotic optimal bound, but also give an integral equation to determine the reference values to arrive at optimality. Simulation results are used to verify the theoretical optimal p...

This work presents an exponentially weighted moving average (EWMA)-based synthesised control scheme for a process with outliers. Based on experience, some processes occasionally have outliers. The use of traditional mean ( X ) and range (R) control charts (denoted as X=R) for monitoring process mean and variance leads to high-level false alarms. In this study, the fast-detection technique (EWMA...

The EWMA chart for the standard deviation is a useful tool for monitoring the variability of a process quality characteristic. The performance of this chart is usually evaluated under the assumption of known parameters. However, in practice, process parameters are estimated from an in-control Phase I data set. A modified EWMA control chart is proposed for monitoring the standard deviation when ...

The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are seriallycorrelated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, s...