Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239438
Title: Artificial intelligence methods in process plant layout
Author: McBrien, Andrew
ISNI:       0000 0001 3622 5672
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 1994
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Abstract:
The thesis describes "Plant Layout System" or PLS, an Expert System which automates all aspects of conceptual layout of chemical process plant, from sizing equipment using process data to deriving the equipment items' elevation and plan positions. PLS has been applied to a test process of typical size and complexity and which encompasses a wide range of layout issues and problems. The thesis presents the results of the tests to show that PLS generates layouts that are entirely satisfactory and conventional from an engineering viewpoint. The major advance made during this work is the approach to layout by Expert System of any kind of process plant. The thesis describes the approach in full, together with the engineering principles which it acknowledges. Plant layout problems are computationally complex. PLS decomposes layout into a sequence of formalised steps and uses a powerful and sophisticated technique to reduce plant complexity. PLS uses constraint propagation for spatial synthesis and includes propagation algorithms developed specifically for this domain. PLS includes a novel qualitative technique to select constraints to be relaxed. A conventional frame based representation was found to be appropriate, but with procedural knowledge recorded in complex forward chaining rules with novel features. Numerous examples of the layout engineer's knowledge are included to elucidate the epistemology of the domain.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.239438  DOI: Not available
Keywords: TP Chemical technology
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