We propose a Shewhart control chart based on gauging theoretically continuous observations into multiple groups. This chart is designed to monitor the process mean and standard deviation for deviations from stability. By assuming an underlying normal distribution, we derive the optimal grouping criteria that maximizes the expected statistical information available in a sample. Control charts ba...

In this study, different ranked-based sampling (RBS) schemes are used to design a sensitive control chart monitor the small or moderate shifts in process mean and named combined EWMA moving average RBS (CEM-RBS) charts. The run-length (ARL) standard deviation of (SDRL) through Monte Carlo simulation runs computed evaluate performance proposed charts comparison with existing such as MA, EWMA, EW...

The purpose of this article is to evaluate the application of forecasting models along with the use of residual control charts to assess production processes whose samples have autocorrelation characteristics. The main objective is to determine the efficiency of control charts for individual observations (CCIO) and exponentially weighted moving average (EWMA) charts when they are applied to res...

(Correction made here after initial online publication.) Today's manufacturing environment has changed since the time when control chart methods were originally introduced. Sequentially observed data are much more common. Serial correlation can seriously affect the performance of the traditional control charts. In this article we derive explicit easy-to-use expressions of the variance of an EWM...

Statistical process control (SPC) is an approach to evaluate processes whether they are in statistical control or not. For this aim, control charts are generally used. Since sample data may include uncertainties coming from measurement systems and environmental conditions, fuzzy numbers and/or linguistic variables can be used to capture these uncertainties. In this paper, one of the most popula...

The Extended Exponentially Weighted Moving Average (extended EWMA) control chart is one of the charts and can be used to quickly detect a small shift. performance evaluated with average run length (ARL). Due deriving explicit formulas for ARL on two-sided extended EWMA trend autoregressive or AR(p) model has not been reported previously. aim this study derive as well AR(1) AR(2) models exponent...

Control charts based on time between events (TBE) data have been shown to be useful for monitoring production or failure processes where defect or failure occurrence can be recorded over time. One type of TBE chart is set up with probability control limits, e.g. the Cumulative Quantity Control (CQC) chart and its extension CQC-r chart, which monitors the quantity inspected until the occurrence ...

The setting of the control limits to utilize on a control chart supposes the assumption of the normality. However, in many situations, this condition does not hold. There are numerous studies on the control charts when the underlying distribution is non-normal. This paper examines the effects of non-normality as measured by skewness and provides an alternative method of designing individuals co...

Many extensions and modifications have been made to standard process monitoring methods such as the exponentially weighted moving average (EWMA) chart cumulative sum (CUSUM) chart. In addition, new schemes proposed based on alternative weighting of past data, usually put greater emphasis data less weight current recent data. other cases, output one method, EWMA statistic, is used input another ...