Statistical process control (SPC) has been used to achieve and maintain control of various processes in industry (Stoumbos, Reynolds, Ryan, and Woodall 2000). The control chart is a primary SPC tool to monitor process variability and promote quality improvement by means of detecting process shifts requiring corrective actions. As a graphical monitor, control charts generally contain a centerlin...

The special causes of variations, which is also known as a shift, can occur in single or more than one related process characteristics. Statistical control tools such charts are useful to monitor shifts the parameters (location and/or dispersion). In real-life situation, shift emerging different sizes, and it hard identify with classical charts. Moreover, characteristics required attention beca...

Control charts for monitoring of process variance are developed based on Shewhart, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts for mean. In all these variance control charts, log transformation of the sample variance is used. The design procedure of this chart is complex and it is poorly understood by the industry. In this paper a EWMA chart for monito...

End-to-end available bandwidth estimation is very important for bandwidth dependent applications, quality-of-service verification and traffic engineering. Although several techniques and tools have been developed in the past, producing precise estimations in real-time still remains challenging, mainly due to the lack of control on the measured network path and environmental conditions, such as ...

The Internet routers employing the random early detection (RED) algorithm for congestion control suffer from the problem of chaotic queue oscillation. It is well known that the slowly varying nature of the average queue size computed using an exponentially weighted moving average (EWMA) used in the RED scheme causes this chaotic behavior. This paper presents a new mathematical function to model...

Recently, monitoring the process mean and variability simultaneously for multivariate processes by using a single control chart has drawn some attention. However, due to the complexity of multivariate distribution, the existing methods in the univariate processes can not be readily extended to the multivariate processes. In this paper, we propose a new single control chart which integrates the ...

Control charts with exponentially weighted moving average (EWMA) statistics (mean and variance) are used to jointly monitor the mean and variance of a process. An EWMA cost minimization model is presented to design the joint control scheme based on pure economic or both economic and statistical performance criteria. The pure economic model is extended to the economic-statistical design by addin...