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Process Data Chemometrics
Authors:
Karlene A.
Hoo, Michael J. Piovoso, and James P. Yuk
Dupont Chemical Co., Wilmington,
DE
Abstract
Data rich
but information poor is an excellent way to characterize most chemical
processes today. The lack of data analysis tools and adequate fundamental and
experimental models makes it difficult to pursure product quality and improved
understanding of a process. One data analysis technique successfully applied
in spectroscopy to reduce a large quantity of data into meaningful
information is Chemometrics. Data when properly interpreted by statistical
data analysis tools and fundamental and heuristic models yield meaningful
information. In this paper we discuss the use of Chemometrics as a
multivariate analyzer to provide a composite measurement of the state of a
chemical process operation. An application of this analyzer on a Du Pont
Plant is presented, and we introduce two measures to detect and identify
important process shifts.
Publication:
IEEE Transactions on Instrumentation
and Measurement, 41:2.,pp 262-268, 1992.
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