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Proceedings Paper

Development Of Knowledge Systems For Trouble Shooting Complex Production Machinery
Author(s): Richard L Sanford; Thomas Novak; James R. Meigs
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Paper Abstract

This paper discusses the use of knowledge base system software for microcomputers to aid repairmen in diagnosing electrical failures in complex mining machinery. The knowledge base is constructed to allow the user to input initial symptoms of the failed machine, and the most probable cause of failure is traced through the knowledge base, with the software requesting additional information such as voltage or resistance measurements as needed. Although the case study presented is for an underground mining machine, results have application to any industry using complex machinery. Two commercial expert-system development tools (M1 TM and Insight 2+TM) and an Al language (Turbo PrologTM) are discussed with emphasis on ease of application and suitability for this study.

Paper Details

Date Published: 11 May 1987
PDF: 9 pages
Proc. SPIE 0786, Applications of Artificial Intelligence V, (11 May 1987); doi: 10.1117/12.940639
Show Author Affiliations
Richard L Sanford, The University of Alabama (United States)
Thomas Novak, The University of Alabama (United States)
James R. Meigs, The University of Alabama (United States)

Published in SPIE Proceedings Vol. 0786:
Applications of Artificial Intelligence V
John F. Gilmore, Editor(s)

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