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...

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...

To monitor time and magnitude, different types of control charts have been proposed in the literature. This article proposes a new maximum exponentially weighted moving average (Max-EWMA) chart by assuming Weibull distribution. The test-statistic Max-EWMA consists two EWMA statistics, where one statistic is used for monitoring magnitude while other to interval between events. performances asses...

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...

In many count data sets, an item may have more than one defect that causes the item to be defective. The Poisson EWMA scheme cannot be used to monitor such defects. The geometric-Poisson exponentially weighted moving average (EWMA) chart has been shown to be an effective scheme to monitor the number of defects over time. In these applications, it is assumed that the process parameters are known...

Monitoring complex production systems is primordial to ensure management, reliability and safety as well as maintaining the desired product quality. Early detection of emergent abnormal behaviour in monitored systems allows pre-emptive action to prevent more serious consequences, to improve system operations and to reduce manufacturing and/or service costs. This study reports the design of a ne...

Guttman and Tiao [1], and Chang [2] showed that the effect of outliers may cause serious bias in estimating autocorrelations, partial correlations, and autoregressive moving average parameters (cited in Chang et al. [3]). This paper presents a modified weighted symmetric estimator for a Gaussian first-order autoregressive AR(1) model with additive outliers. We apply the recursive median adjustm...