Serel, D. A.2016-02-082016-02-0820090895-7177http://hdl.handle.net/11693/22843For monitoring the stability of a process, various control charts based on exponentially weighted moving average (EWMA) statistics have been proposed in the literature. We study the economic design of EWMA-based mean and dispersion charts when a linear, quadratic, or exponential loss function is used for computing the costs arising from poor quality. The chart parameters (sample size, sampling interval, control limits and smoothing constant) minimizing the overall cost of the control scheme are determined via computational methods. Using numerical examples, we compare the performances of the EWMA charts with Shewhart over(X, -) and S charts, and investigate the sensitivity of the chart parameters to changes in process parameters and loss functions. Numerical results imply that rather than sample size or control limits, the users need to adjust the sampling interval in response to changes in the cost of poor quality.EnglishAverage run lengthEconomic designEWMA control chartMarkov chainStatistical process controlDesignDigital signal processingFlowchartingFunctionsGraphic methodsMarkov processesProbability density functionProcess controlProcess engineeringQuality controlSurface treatmentAverage run lengthControl chartsControl limitsControl schemesEconomic designEwma chartsEWMA control chartExponential loss functionsExponentially weighted moving averagesIn processesLoss functionsMarkov chainNumerical examplesNumerical resultsOverall costsSample sizesSampling intervalsShewhartSmoothing constantsStatistical process controlArticle10.1016/j.mcm.2008.06.012