The control chart is a very popular tool of statistical process control. It is used to determine the existence of special cause variation to remove it so that the process may be brought in statistical control. Shewhart-type control charts are sensitive for large disturbances in the process, whereas cumulative sum (CUSUM)–type and exponentially weighted moving average (EWMA)–type control charts ...

• The usual CUSUM chart for the mean (CUSUM-X̄) is a chart used to quickly detect small to moderate shifts in a process. In presence of outliers, this chart is known to be more robust than other mean-based alternatives like the Shewhart mean chart but it is nevertheless affected by these unusual observations because the mean (X̄) itself is affected by the outliers. An outliers robust alternative ...

The control chart is an important statistical technique that is used to monitor the quality of a process. Shewhart control charts are used to detect larger disturbances in the process parameters, whereas CUSUM and EWMA charts are meant for smaller and moderate changes. Runs rules schemes are generally used to enhance the performance of Shewhart control charts. In this study, we propose two runs...

Security is one of the most important research issues in wireless sensor networks (WSN) applications. Given that the single detection threshold of the cumulative sum (CUSUM) algorithm causes longer detection delays and a lower detection rate, a multi-class CUSUM algorithm is hereby proposed. Firstly a maximum and minimum thresholds, which sensor nodes are able to reach during sending packet, ar...

Security is one of the most important research issues in wireless sensor networks (WSN) applications. Given that the single detection threshold of the cumulative sum (CUSUM) algorithm causes longer detection delays and a lower detection rate, a multi-class CUSUM algorithm is hereby proposed. Firstly a maximum and minimum thresholds, which sensor nodes are able to reach during sending packet, ar...

C-control chart assumes that process nonconformities follow a Poisson distribution. In actuality, however, this Poisson distribution does not always occur. A process control for semiconductor based on a Poisson distribution always underestimates the true average amount of nonconformities and the process variance. Quality is described more accurately if a compound Poisson process is used for pro...

Introduction Since the release of anthrax in October of 2001, there has been increased interest in developing efficient prospective disease surveillance schemes. Poisson CUSUM is a control chart-based method that has been widely used to detect aberrations in disease counts in a single region collected over fixed time intervals. Over the past few years, different methods have been proposed to ex...

In order to monitor a process, quality practitioners frequently use Shewhart control charts (e.g. X –R, P-charts, etc.), so named after the pioneering work of Dr. Walter Shewhart. It can be shown that if there are sharp, intermittent changes to a process, these types of charts are highly effective. However, if one is interested in a small, sustained shift in a process, other types of control ch...

C-control chart assumes that process nonconformities follow a Poisson distribution. In actuality, however, this Poisson distribution does not always occur. A process control for semiconductor based on a Poisson distribution always underestimates the true average amount of nonconformities and the process variance. Quality is described more accurately if a compound Poisson process is used for pro...

BACKGROUND The automated monitoring of routinely collected disease surveillance data has the potential to ensure that important changes in disease incidence are promptly recognised. However, few studies have established whether the signals produced by automated monitoring methods correspond with events considered by epidemiologists to be of public health importance. This study investigates the ...