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Proceedings Paper

Knowledge-based diagnostic problem solving and learning in the test area of electronics assembly manufacturing
Author(s): S. Narayanan; Ashwin Ram; Sally M. Cohen; Christine M. Mitchell; T. Govindaraj
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Paper Abstract

A critical area in electronics assembly manufacturing is the test and repair area. Computerized decision aids at this area can facilitate enhanced system performance. A key to developing computer-based aids is gaining an understanding of the human problem solving process in the complex task of troubleshooting in electronics manufacturing. In this paper, we present a computational model of troubleshooting and learning in electronics assembly manufacturing. The model is based on a theory of knowledge representation, reasoning, and learning, which is grounded in observations of human problem solving. The theory provides a foundation for developing applications of AI in complex, real world domains.

Paper Details

Date Published: 1 March 1992
PDF: 10 pages
Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); doi: 10.1117/12.56876
Show Author Affiliations
S. Narayanan, Georgia Institute of Technology (United States)
Ashwin Ram, Georgia Institute of Technology (United States)
Sally M. Cohen, Georgia Institute of Technology (United States)
Christine M. Mitchell, Georgia Institute of Technology (United States)
T. Govindaraj, Georgia Institute of Technology (United States)


Published in SPIE Proceedings Vol. 1707:
Applications of Artificial Intelligence X: Knowledge-Based Systems
Gautam Biswas, Editor(s)

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