The generally weighted moving average (GWMA) control chart is an extension model of exponentially weighted moving average (EWMA) control chart. Recently, some approaches have been proposed to modify EWMA charts with fast initial response (FIR) features. We introduce these approaches in GWMA-type...

The conventional Shewhart p or np chart is not effective for monitoring a high yield process, a process in which the defect level is close to zero. An improved Shewhart np chart for monitoring high yield processes is proposed. A review of control charts for monitoring high yield processes is...

The np control chart is used widely in Statistical Process Control (SPC) for attributes. It is difficult to design an np chart that simultaneously satisfies a requirement on false alarm rate and has high detection effectiveness. This is mainly because one is often unable to make the in-control...

This article analyses the performance of a one-sided cumulative sum (CUSUM) chart that is initialized using a random starting point following the natural or intrinsic probability distribution of the CUSUM statistic. By definition, this probability distribution remains stable as the chart is...

The effects of parameter estimation are examined for the well-known c-chart for attributes data. The exact run length distribution is obtained for Phase II applications, when the true average number of non-conformities, c, is unknown, by conditioning on the observed number of non-conformities in...

Measurement error is a usually met distortion factor in real-world applications that influences the outcome of a process. In this paper, we examine the effect of measurement error on the ability of the EWMA control chart to detect out-of-control situations. The model used is the one involving...

Exponentially weighted moving average (EWMA) plans for non-homogeneous negative binomial counts are developed for detecting the onset of seasonal disease outbreaks in public health surveillance. These plans are robust to changes in the in-control mean and over-dispersion parameter of the...

Few approaches for monitoring autocorrelated attribute data have been proposed in the literature. If the marginal process distribution is binomial, then the binomial AR(1) model as a realistic and well-interpretable process model may be adequate. Based on known and newly derived statistical...

This paper discusses the development of a multivariate control charting technique for short-run autocorrelated data manufacturing environment. The proposed approach is a combination of the multivariate residual charts for autocorrelated data and the multivariate transformation technique for...

In this paper, an attempt is made to develop Quality Control Charts for monitoring the process mean based on Double Ranked Set Sampling (DRSS) rather than the traditional Simple Random Sampling (SRS). Considering a normal population and several shift values, the performance of the Average Run...