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Proceedings Paper

Vision of neural networks and fuzzy logic for prediction and optimization of manufacturing processes
Author(s): James D. Keeler
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Paper Abstract

The advent of low cost, reliable sensor technology and ongoing dramatic improvements in computer price/performance have transformed the average manufacturing facility into a data- rich environment with millions of bytes of production information stored daily. This production data contains valuable information about the process that can be used by a neural network to model, control, and optimize the plant dynamics. This paper presents a perspective on the use of neural networks and fuzzy logic technology and outlines the methods that have been used to improve process performance in several applications in chemical/petrochemical production facilities.

Paper Details

Date Published: 16 September 1992
PDF: 10 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.140022
Show Author Affiliations
James D. Keeler, Pavilion Technologies, Inc. (United States)


Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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