Abstract
There are two major approaches in dealing with autocorrelated process data in process control, that is, residual-based approaches and methods that modify control limits to adjust for autocorrelation. We proposed a methodology for constructing control charts for autocorrelated process data using the AR-sieve bootstrap. The simulation study illustrates the relative advantage of the AR-sieve bootstrap control chart with respect to the in-control and out-of-control run length and false alarm rate. The proposed methodology works even for small sample sizes and conditions of the near nonstationarity of the generating process. The proposed AR-sieve bootstrap control chart presents the advantage of being distribution-free for certain class of linear models as well as the tracking of actual process observations instead of model residuals, thus facilitating the implementation during actual plant operations.
Original language | English (US) |
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Pages (from-to) | 387-395 |
Number of pages | 9 |
Journal | Quality and Reliability Engineering International |
Volume | 28 |
Issue number | 4 |
DOIs | |
State | Published - Jun 2012 |
Externally published | Yes |
Keywords
- AR-sieve bootstrap
- autocorrelated process
- distribution-free control chart
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Management Science and Operations Research