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Purpose The purpose of this paper is to introduce and investigate the performances of a new CUSUM‐S2 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‐S2 chart has been assessed through a comparison with an EWMA‐S2 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‐S2 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‐S2 control chart allows a decreasing of the variability to be detected faster than the corresponding EWMA‐S2 control chart proposed earlier in the literature.
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Stored only when both papers are in the corpus — 40 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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