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Proceedings Paper

A Knowledge-Based Manufacturing System Using OSAM
Author(s): D. K. Desai; S. Pal; S. B. Navathe; K. L. Doty
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Paper Abstract

Manufacturing industries have greatly emphasized the need to "integrate" various manufacturing functions-Design, Planning, and Business Operations- into a unified and well coordinated system, so as to increase productivity. In order to achieve this goal, the various CAD/CAM systems must have a common engineering and manufacturing knowledge base. We propose a Knowledge Based Manufacturing System(KBMS) that will help the Manufacturing Engineer(ME) to directly model the workcell environment. The system consists of two main modules: the Workcell Modelling Facility and the Task Planner. The Workcell Modelling Facility helps the ME to create workcell models using the workcell components, product parts, and manufacturing operations contained in a pre-defined knowledge base. The system also allows the manufacturing engineer to add information to the existing knowledge bases schemas. The Task Planner accesses these knowledge bases to generate a network of proposed actions from a given production goal. Integration of the proposed KBMS with a Geometric Modelling System will provide the ME with a tool to perform off-line animation of the Manufacturing Process in a particular workcell model. A prototype KBMS is currently being implemented at the University of Florida using the Object-oriented Semantic Association Model(OSAM*) as the underlying data model for the Knowledge Bases. OSAM* provides the object-oriented features of inheritance and encapsulation of data, as well as the ability to represent complex relationships between object classes in semantic nets.

Paper Details

Date Published: 9 February 1989
PDF: 15 pages
Proc. SPIE 1008, Expert Robots for Industrial Use, (9 February 1989); doi: 10.1117/12.949131
Show Author Affiliations
D. K. Desai, The University of Florida (United States)
S. Pal, The University of Florida (United States)
S. B. Navathe, The University of Florida (United States)
K. L. Doty, The University of Florida (United States)

Published in SPIE Proceedings Vol. 1008:
Expert Robots for Industrial Use
David P. Casasent; Ernest L. Hall; Kenneth J. Stout, Editor(s)

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