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.
Recommended Citation
T. A. Stelljes and K. T. Erickson, "Modeling the Quality of Steel Production with an Adaptive Logic Network," Proceedings of the Artificial Neural Networks in Engineering Conference (1995, St. Louis, MO), vol. 5, pp. 943 - 948, American Society of Mechanical Engineers (ASME), Nov 1995.
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.
Publication Date
01 Nov 1995
