Title

Modeling the Quality of Steel Production with an Adaptive Logic Network

Abstract

An Adaptive Logic Network, a simplified, special case of the multilayer perceptron feedforward neural network, is used to model the off-line evaluation of the quality of a ball steel production line providing grinding media for the mining industry. The model developed in this project predicts the proportion of rejected bars in a cast based on significant information recorded during the process. The results of this application suggest that this method may be a faster way to develop a usable model for off-line analysis than conventional methods.

Meeting Name

Artificial Neural Networks in Engineering Conference, ANNIE (1995: Nov. 12-15, St. Louis, MO)

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Bars (Metal); Computer Integrated Manufacturing; Iron and Steel Plants; Mathematical Models; Multilayer Neural Networks; Quality Control; Steelmaking; Adaptive Logic Networks; Feedforward Neural Networks

International Standard Book Number (ISBN)

0-7918-0048-2

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1995 American Society of Mechanical Engineers (ASME), All rights reserved.

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