The control limits of an exponentially weighted moving average (EWMA) control chart should vary with time, approaching asymptotic limits as time increases. However, previous analytic analyses of EWMA charts consider only asymptotic control limits. In this article, the run length properties of EWMAs with time-varying control limits are approximated using nonhomogeneous Markov chains. Comparing t...

Methodology is presented for the design of single and double compressed limit Sequential Probability Ratio Tests (SPRT) and Cumulative Sum (CUSUM) control charts to detect one-sided mean shifts in a symmetric probability distribution. We also show how to evaluate the average run length properties with the Fast Initial Response (FIR) feature. The resulting CUSUM plans have a simple scoring proce...

This paper presents the analysis of a renewal input  finite buffer queue wherein the customers can decide either to  join the queue with a probability or balk. The service process is Markovian service process ($MSP$) governed  by an underlying $m$-state Markov chain. Employing the supplementary  variable and imbedded Markov chain techniques,   the steady-state system length distributions at pre...

We propose a new multivariate CUSUM control chart, which is based on selfadaption of its reference value according to the information of current process readings, to quickly detect the multivariate process mean shifts. By specifying the minimum magnitude of the process mean shift in terms of its non-centrality parameter, our proposed control chart can achieve an overall performance for detectin...

The cumulative sum (CUSUM) chart, well-known to be sensitive in detecting small and moderate parameter changes, is proposed here for monitoring a high yield process. The sensitivities of the CUSUM charts based on geometric, Bernoulli and binomial counts are compared. Based on the comparisons, recommendations for the selection of a chart are provided. Simple procedures are given for optimal desi...

Precise identification of the time when a process has changed enables process engineers to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for a Poisson process in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step < /div> change, a linear trend and a known multip...

We study the entropy rate of a hidden Markov process, defined by observing the output of a symmetric channel whose input is a first order Markov process. Although this definition is very simple, obtaining the exact amount of entropy rate in calculation is an open problem. We introduce some probability matrices based on Markov chain's and channel's parameters. Then, we try to obtain an estimate ...

Economic design of multivariate exponentially weighted moving average (MEWMA) control charts for monitoring the process mean vector involves determining economically the optimum values of the three control parameters: the sample size, the sampling interval between successive samples, and the control limits or the critical region of the chart. In the economic-statistical design, constraints (inc...

Quality control is an important role in industry for maintain quality stability. Statistical process can quickly investigate the occurrence of unforeseen causes or shifts using charts. Mixed Exponentially Weighted Moving Average - Cumulative Sum (MEC) chart a tool used to monitor and evaluate whether production not. The MEC method combination (EWMA) (CUSUM) Combining two charts aims increase se...

A cumulative sum (CUSUM) control chart is one of the most popular methods used to detect a process mean shift. When one specific size of the mean shift is assumed, the CUSUM chart can be optimally designed in terms of average run length (ARL). In practice, however, the size of the mean shift is usually unknown, and the CUSUM chart can perform poorly when the actual size of the mean shift is sig...