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An expert system based aid for anode production at an aluminium smelter

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Gale, Paul H (1997) An expert system based aid for anode production at an aluminium smelter. Research Master thesis, University of Tasmania.

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Abstract

In the smelting of aluminium, a high current is passed between an anode and a cathode
across a molten bath of electrolyte. As the anode is consumed in the electrolytic
process, the manufacture of anodes represents a high operational cost. Better control
of the anode production process could lead to a reduction in the variability of anode
qualities, improved anode performance and a resulting longer anode life with a
concomitant reduction in operational costs.
The production process of anodes is controlled by operators through a Supervisory
Control and Data Acquisition (SCADA) system that continuously polls the front line
program logic control of the anode plant. Information relating to potential problems
or causes of existing problems is available, which an experienced operator can obtain
by querying the SCADA system. As there is too much data for the operator to
assimilate to properly control the process, the operator tends to rely on the control
system itself to control the process within its own limitations, since more pressing
problems usually divert him from this fine tuning task. Thus, anodes are produced that
generally meet specification, but with some degree of variability.
The work presented in this thesis addresses the use of artificial intelligence techniques
to develop a decision support system for use by the anode plant operators. Research
focused on the following issues:
• identification of the process parameters that critically affect an anode's
properties;
• determination of the problems, and their causes, that affect those process
parameters;
• determination of the most appropriate way to present information to the
operator;
• development of the required software;
• determination of the best methods, in terms of speed and PC memory, of
exchanging data with SCADA;
• development of a robust application that runs continuously, without failure, for
a ten day production run.
The developed application, based on Level5 Object software, continuously
interrogates the process control system and provides on-line analysis to operators of
ten process variables identified as critically affecting anode properties. For each
process variable, are displayed a triplet of statistical process control charts and
messages advising of trends, potential problems and possible causes of those
problems. Utilising hypertext, the operator can view and print out a Standard
Operating Procedure to rectify said problem. Properly used, the monitor provides the
operator with a high level tool to enable anodes to be made to a consistent quality
within tight process limits.
The research has established the necessary techniques to design a system to
continuously oversee and monitor a complex production process, to analyse large
amounts of data in real time and to provide meaningful and timely information to the
operator to enable the application of the necessary corrective action. The developed
system has been installed for live monitoring of the process by technical personnel
during 1996 and for operator use in 1997.
Two refereed papers have been published and presented at international conferences.

Item Type: Thesis (Research Master)
Copyright Holders: The Author
Copyright Information:

Copyright 1997 the Author - The University is continuing to endeavour to trace the copyright owner(s) and in the meantime this item has been reproduced here in good faith. We would be pleased to hear from the copyright owner(s).

Additional Information:

Addresses the use of artificial intelligence techniques to develop a decision support system for use by anode plant operators. The developed application, based on Level15 Object software, continuously interrogates the process control system and provides on-line analysis to operators of ten process variables identified as critically affecting anode properties. No access until 1.6.1998. Thesis (M.Eng.Sc.)--University of Tasmania, 1998. Includes bibliographical references. Addresses the use of artificial intelligence techniques to develop a decision support system for use by anode plant operators. The developed application, based on Level15 Object software, continuously interrogates the process control system and provides on-line analysis to operators of ten process variables identified as critically affecting anode properties

Date Deposited: 09 Dec 2014 00:02
Last Modified: 16 Aug 2016 23:08
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