Abstract

This paper presents an overview of different chaos theory based techniques that may be employed for process monitoring; specifically for monitoring of manufacturing processes. Most process monitoring systems involve estimating certain unknown state variables from the known sensor measurements. This estimation scheme requires mathematically relating the measured time-series data (TSD) from sensor signals to unknown state variables. In order to systematically establish this relationship, knowledge of the process dynamics is essential. Since the dynamics of many manufacturing processes is very likely to be nonlinear, the use of chaos theory is relevant for process monitoring. This paper describes various chaos theory based techniques employed in process monitoring systems.

Original languageEnglish (US)
Pages223-228
Number of pages6
StatePublished - Dec 1 1996
EventProceedings of the 1996 5th Industrial Engineering Research Conference - Minneapolis, MN, USA
Duration: May 18 1996May 20 1996

Other

OtherProceedings of the 1996 5th Industrial Engineering Research Conference
CityMinneapolis, MN, USA
Period5/18/965/20/96

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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