The combination of Shewhart control charts and an exponentially weighted moving average (EWMA) control charts to simultaneously monitor shifts in the mean output of a production process has proven very effective in handling both small and large shifts. To improve the sensitivity of the control chart to detect off-target processes, we propose a combined Shewhart-EWMA (CSEWMA) control chart for m...

OBJECTIVE This study aims to compare different control charts to monitor the nosocomial infection rate per 1,000 patient-days. METHODS The control charts considered in this study were the traditional Shewhart chart and a variation of this, the Cumulative Sum and Exponentially Weighted Moving Average charts. RESULTS We evaluated 238 nosocomial infections that were registered in the intensive...

A Cumulative Sum (CUSUM) control chart capable of detecting changes in both the mean and the standard deviation for autocorrelated data, referred to as the Max-CUSUM chart for Autocorrelated Process chart (MCAP chart), is proposed. This chart is based on fitting a time series model to the data, and then calculating the residuals. The observations are represented as a first-order autoregressive ...

Statistical Process Control (SPC) is used to monitor the process stability which ensures the predictability of the process. In 1920‟s Shewhart introduced the control chart techniques that are one of the most important techniques of quality control to detect if assignable causes exist. The widely used control chart techniques are R X  and S X  . These are called traditional variable control ch...

Parameter estimation causes a considerable stochastic error in standard Shewhart charts. This problem can be solved using suitable correction factors. But if the normality assumption itself fails, in addition a nonvanishing model error will occur. By then, a nonparametric alternative, such as the recently proposed MIN chart, might be a better idea throughout. However, for those reluctant to giv...

The Shewhart, Bonferroni-adjustment and analysis of means (ANOM) control chart are typically applied to monitor the mean of a quality characteristic. The Shewhart and Bonferroni procedure are utilized to recognize special causes in production process, where the control limits are constructed by assuming normal distribution for known parameters (mean and standard deviation), and approximately no...

The Shewhart control chart is for many people the embodiment of statistical process control (SPC). In the past, many modifications and improvements have been devised (see Woodall and Montgomery [1999] for a brief overview). Several modifications or additions were aimed at more power for out-of-control situations. Among the earlier additions belong the runs rules from the Western Electric Compan...

Statistical process control (SPC) requires statistical methodologies that detect changes in the pattern of data over time. The common methodologies, such as Shewhart, cumulative sum (cusum), and exponentially weighted moving average (EWMA) charting, require the in-control values of the process parameters, but these are rarely known accurately. Using estimated parameters, the run length behavior...

The design of control charts in statistical quality control addresses the optimal selection of the design parameters such as the sampling frequency and the control limits; and includes sensitivity analysis with respect to system parameters such as the various process parameters and the economic costs of sampling. The advent of more complicated control chart schemes has necessitated the use of M...