Data mining in a chemical process application

Author

Mastrangelo, C.M. ; Porter, J.M.

Author_Institution

Dept. of Syst. Eng., Virginia Univ., Charlottesville, VA, USA

Volume

3

fYear

1998

fDate

11-14 Oct 1998

Firstpage

2917

Abstract

In an effort to increase the quality of a product, manufacturers employ a variety of tools, including statistical process monitoring. The recent revolution in sensor technology results in a deluge of data, but little process information. This domain is ripe for multivariate process monitoring. Traditionally, research focused on developing control chart statistics and not on the selection of key process variables. This paper utilizes various data mining methodologies to determine the driving variables in a continuous manufacturing process

Keywords

chemical engineering computing; computerised monitoring; data mining; manufacturing processes; statistical process control; chemical process application; continuous manufacturing process; control chart statistics; data mining; multivariate process monitoring; product quality; sensor technology; statistical process monitoring; Chemical processes; Computerized monitoring; Data mining; Input variables; Manufacturing processes; Optical fiber sensors; Optical fiber testing; Production; Scanning probe microscopy; Synthetic fibers;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on

Conference_Location

San Diego, CA

ISSN

1062-922X

Print_ISBN

0-7803-4778-1

Type

conf

DOI

10.1109/ICSMC.1998.725106

Filename

725106