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Deciles‐based EWMA‐type sign charts for process dispersion.

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Title: Deciles‐based EWMA‐type sign charts for process dispersion.
Authors: Godase, Dadasaheb G.1 (AUTHOR), Rakitzis, Athanasios C.2 (AUTHOR) arakitz@unipi.gr, Mahadik, Shashibhushan B.1 (AUTHOR), Khoo, Michael B. C.3 (AUTHOR)
Source: Quality & Reliability Engineering International. Nov2022, Vol. 38 Issue 7, p3726-3740. 15p.
Subjects: Monte Carlo method, Quality control charts, Dispersion (Chemistry), Statistical process control, Moving average process
Abstract: In this paper, we propose and study nonparametric exponentially weighted moving average (EWMA) control charts based on the sign statistic, which are suitable for detecting changes in process dispersion. The sign statistic is defined by using appropriate deciles of the in‐control process distribution. The statistical performances of the proposed charts are determined through Monte Carlo simulation. Practical guidelines are provided for the statistical designs of these charts. We evaluate the statistical performances of the proposed charts by comparing them with that of the deciles‐based CUSUM sign chart and the EWMA lnS2 chart. The comparisons show that the proposed charts are viable nonparametric methods for monitoring the process dispersion. Finally, we provide an illustrative example to demonstrate the implementation of the proposed charts in practice. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:In this paper, we propose and study nonparametric exponentially weighted moving average (EWMA) control charts based on the sign statistic, which are suitable for detecting changes in process dispersion. The sign statistic is defined by using appropriate deciles of the in‐control process distribution. The statistical performances of the proposed charts are determined through Monte Carlo simulation. Practical guidelines are provided for the statistical designs of these charts. We evaluate the statistical performances of the proposed charts by comparing them with that of the deciles‐based CUSUM sign chart and the EWMA lnS2 chart. The comparisons show that the proposed charts are viable nonparametric methods for monitoring the process dispersion. Finally, we provide an illustrative example to demonstrate the implementation of the proposed charts in practice. [ABSTRACT FROM AUTHOR]
ISSN:07488017
DOI:10.1002/qre.3169