A regression control chart for autocorrelated processes

Aslan Deniz Karaoglan and Gunhan Mirac Bayhan

International Journal of Industrial and Systems Engineering, 2014, vol. 16, issue 2, 238-256

Abstract: In this study, we present a new regression control chart which is able to detect the mean shift in a production process. This chart is designed for autocorrelated process observations having a linearly increasing trend. Existing approaches may individually cope with autocorrelated and trending data. The proposed chart requires the identification of trend stationary first order autoregressive (trend AR(1)) model as a suitable time series model for process observations. For a wide range of possible shifts and autocorrelation coefficients, performance of the proposed chart is evaluated by simulation experiments. Average correct signal rate and average run length are used as performance criteria.

Keywords: quality control; statistical process control; SPC; autocorrelation; linear trend; trend AR(1); regression control charts; mean shift; simulation. (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=58838 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:16:y:2014:i:2:p:238-256

Access Statistics for this article

More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().