Title :
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
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4778-1
DOI :
10.1109/ICSMC.1998.725106
