EconPapers    
Economics at your fingertips  
 

Time series analysis of process data

John K. Mahaney, Jr., David Lee Baker and James H. Hamburg

International Journal of Operational Research, 2007, vol. 2, issue 3, 231-253

Abstract: Statistical Process Control (SPC) is an integral component of almost every industrial process, and proper outlier (i.e., out of control) detection is crucial if processes are to remain in statistical control. The goal of this research is to determine whether a simple model may be useful as an approximation to a more exact and thus more difficult model; and still provide sufficient accuracy in outlier detection. We test an ARMA (1,1) model with the Chen and Liu (1993) Joint Estimation (JE) outlier detection algorithm with different sets of process data. We find that this approach is quite useful, especially for practitioners.

Keywords: ARMA (1,1); control charting; joint estimation analysis; JE; outlier detection; process data; statistical process control; SPC; time series analysis; process data; operational research. (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.inderscience.com/link.php?id=12851 (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:ijores:v:2:y:2007:i:3:p:231-253

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijores:v:2:y:2007:i:3:p:231-253