Statistical process monitoring for dynamic systems

Douglas Montgomery, Christina M. Mastrangelo, Cynthia A. Lowry

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In many production processes, particularly those in the chemical and process industries, process variables are driven by inertial forces and thus exhibit dynamic behavior. In some cases these dynamic distributions may be offset by a feedback/feedforward control scheme, while in others, compensation may not be fully possible, and considerable dynamic fluctuation in key process variables may still remain. This paper discusses statistical process monitoring for such systems considering both univariate and multivariate cases.

Original languageEnglish (US)
Title of host publicationProceedings of the Industrial Engineering Research Conference
EditorsDeborah A. Mitta, Laura I. Burke, John R. English, Jennie Gallimore, Georgia-Ann Klutke, Gregory L. Tonkay
PublisherPubl by IIE
Pages559-563
Number of pages5
ISBN (Print)0898061326
StatePublished - Dec 1 1993
EventProceedings of the 2nd Industrial Engineering Research Conference - Los Angeles, CA, USA
Duration: May 26 1993May 28 1993

Publication series

NameProceedings of the Industrial Engineering Research Conference

Other

OtherProceedings of the 2nd Industrial Engineering Research Conference
CityLos Angeles, CA, USA
Period5/26/935/28/93

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Montgomery, D., Mastrangelo, C. M., & Lowry, C. A. (1993). Statistical process monitoring for dynamic systems. In D. A. Mitta, L. I. Burke, J. R. English, J. Gallimore, G-A. Klutke, & G. L. Tonkay (Eds.), Proceedings of the Industrial Engineering Research Conference (pp. 559-563). (Proceedings of the Industrial Engineering Research Conference). Publ by IIE.