Purpose – The purpose of this paper is to introduce and investigate the performances of a new CUSUM-S 2 control chart designed to monitor the sample variance of samples from a normally distributed population. Design/methodology/approach – The proposed chart monitors a statistic computed as a logarithmic transformation of the sample variance; the introduction of the sample variance logarithmic transformation has a twofold effect: to quickly detect the occurrence of an “out-of-control” condition; to deal with a quasi-standard normal statistic. Findings – A design strategy trying to minimize the “out-of-control” average run length (ARL) of the chart is presented and the statistical performance of the CUSUM-S 2 chart has been assessed through a comparison with an EWMA-S 2 control chart proposed in the literature to monitor the process dispersion. Research limitations/implications – The paper only deals with uncorrelated normally distributed data. Practical implications – The obtained results show how the CUSUM-S 2 chart is particularly suitable when reduction in the process dispersion should be detected by means of subgroups having limited sample sizes. Originality/value – The paper shows the new CUSUM-S 2 control chart allows a decreasing of the variability to be detected faster than the corresponding EWMA-S 2 control chart proposed earlier in the literature.
A new CUSUM-S2 control chart for monitoring the process variance
CELANO, GIOVANNI;FICHERA, Sergio
2009-01-01
Abstract
Purpose – The purpose of this paper is to introduce and investigate the performances of a new CUSUM-S 2 control chart designed to monitor the sample variance of samples from a normally distributed population. Design/methodology/approach – The proposed chart monitors a statistic computed as a logarithmic transformation of the sample variance; the introduction of the sample variance logarithmic transformation has a twofold effect: to quickly detect the occurrence of an “out-of-control” condition; to deal with a quasi-standard normal statistic. Findings – A design strategy trying to minimize the “out-of-control” average run length (ARL) of the chart is presented and the statistical performance of the CUSUM-S 2 chart has been assessed through a comparison with an EWMA-S 2 control chart proposed in the literature to monitor the process dispersion. Research limitations/implications – The paper only deals with uncorrelated normally distributed data. Practical implications – The obtained results show how the CUSUM-S 2 chart is particularly suitable when reduction in the process dispersion should be detected by means of subgroups having limited sample sizes. Originality/value – The paper shows the new CUSUM-S 2 control chart allows a decreasing of the variability to be detected faster than the corresponding EWMA-S 2 control chart proposed earlier in the literature.File | Dimensione | Formato | |
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S2Cusum_JQME2009.pdf
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