16 September 1992 Vision of neural networks and fuzzy logic for prediction and optimization of manufacturing processes
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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.
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James D. Keeler, "Vision of neural networks and fuzzy logic for prediction and optimization of manufacturing processes", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.140022; https://doi.org/10.1117/12.140022
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