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 language | English |
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Pages (from-to) | 364-394 |
Number of pages | 31 |
Journal | Production and Manufacturing Research |
Volume | 7 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2019 |
Keywords
- Autocorrelated
- average run length (ARL)
- bootstrap
- maximum MCUSUM (Max-MCUSUM) control chart
- multioutput least square SVR (MLS-SVR)