in this paper, first the available single charting methods, which have been proposed to detect simultaneous shifts in a single process mean and variance, are reviewed. then, by designing proper simulation studies these methods are evaluated in terms of in-control and out-ofcontrol average run length criteria (arl). the results of these simulation experiments show that the ewma and ewms methods ...

in this research, an iterative approach is employed to recognize and classify control chart patterns. to do this, by taking new observations on the quality characteristic under consideration, the maximum likelihood estimator of pattern parameters is first obtained and then the probability of each pattern is determined. then using bayes’ rule, probabilities are updated recursively. finally, when...

control chart is the most well-known chart to monitor the number of nonconformities per inspection unit where each sample consists of constant size. generally, the design of a control chart requires determination of sample size, sampling interval, and control limits width. optimally selecting these parameters depends on several process parameters, which have been considered from statistical and...

Background and objectives: Risk-adjusted Bernoulli control chart is one of the main tools for monitoring multistage healthcare processes to achieve higher performance and effectiveness in healthcare settings. Using parameter estimates can lead to significantly deteriorate chart performance. However, so far, the effect of estimation error on this chart in which healthcare ...

Control charts are the most important tools of statistical process control used to discriminate between assignable and common causes of variation and to improve the quality of a process. To design a control chart, three parameters including sample size, sampling interval, and control limits should be determined. The objectives are hourly expected cost, in-control average run length, power of th...