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- Title
An AR-Sieve Bootstrap Control Chart for Autocorrelated Process Data.
- Authors
Mancenido, Michelle; Barrios, Erniel
- 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. Copyright © 2011 John Wiley & Sons, Ltd.
- Subjects
AUTOCORRELATION (Statistics); STATISTICAL correlation; STOCHASTIC processes; LINEAR statistical models; MATHEMATICAL statistics; MATHEMATICAL models
- Publication
Quality & Reliability Engineering International, 2012, Vol 28, Issue 4, p387
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.1253