Residual-based maximum MCUSUM control chart for joint monitoring the mean and variability of multivariate autocorrelated processes

Hidayatul Khusna, Muhammad Mashuri*, Suhartono, Dedy Dwi Prastyo, Muhammad Hisyam Lee, Muhammad Ahsan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Maximum multivariate cumulative sum (Max-MCUSUM) is one of the single control charts proposed for joint monitoring the mean and variability of independent observation. Since many applications yield time series data, it is important to develop Max-MCUSUM control chart for monitoring multivariate autocorrelated processes. In this paper, we propose a Max-MCUSUM control chart based on the residual of multioutput least square support vector regression (MLS-SVR). The optimal parameters of MLS-SVR model are calculated using historical in-control data and the control limit of the proposed chart is estimated using the bootstrap approach. The average run lengths of MLS-SVR-based Max-MCUSUM chart verify that the proposed chart is more sensitive to detect mean vector shift than to detect a covariance matrix shift. The illustrative examples of the proposed control chart are also provided for both simulation and real data.

Original languageEnglish
Pages (from-to)364-394
Number of pages31
JournalProduction and Manufacturing Research
Volume7
Issue number1
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • Autocorrelated
  • average run length (ARL)
  • bootstrap
  • maximum MCUSUM (Max-MCUSUM) control chart
  • multioutput least square SVR (MLS-SVR)

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