Industrial application of neural networks - An investigation

B. Lennox, G. A. Montague, A. M. Frith, C. Gent, V. Bevan

    Research output: Contribution to journalArticlepeer-review

    Abstract

    This paper summarises a 2-year industrial investigation into the application of artificial neural networks in the area of process monitoring and control. The investigation was a collaborative programme between the University of Newcastle-upon-Tyne, EDS and 24 UK based international companies. Descriptions of the major activities undertaken in this programme, which included the application of neural networks for fault detection in a vitrification process and the model based predictive control of a gasoline engine are provided. The paper also describes some of the practical difficulties that were experienced while applying neural networks and lists the important lessons that were learned through the completion of this project. The main conclusion from the work was that neural networks are capable of improving industrial process monitoring and control systems. However, the level of improvement must be analysed on a problem specific basis and in many applications the use of neural networks may not be justifi ed. © 2001 Elsevier Science Ltd. All rights reserved.
    Original languageEnglish
    Pages (from-to)497-507
    Number of pages10
    JournalJournal of Process Control
    Volume11
    Issue number5
    DOIs
    Publication statusPublished - Oct 2001

    Keywords

    • Artificial neural networks
    • Process control
    • Process monitoring
    • System identification

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