A Two-Phase Robust Estimation of Process Dispersion Using M-estimator

Parameter estimation is the first step in constructing any control chart. most estimators of meanand dispersion are sensitive to the presence of outliers. the data may be contaminated byoutliers either locally or globally. the exciting robust estimators deal only with globalcontamination. in this paper a robust estimator for dispersion is proposed to reduce the effect oflocal contamination when estimating the parameters. the results have shown that the introducedestimator is more precise in estimating the dispersion when there are outliers within thesubgroups. simulation results indicate that robustness and efficiency of the proposed dispersionestimator is considerably high and its sensitivity to the changes in mean and standard deviationof any subgroup is roughly lower than the other estimators being compared.