Knowledge representation and control structure based on three-dimensional symbolic skeletons for CAD/CAM integration

Authors:
I. C. You;C. N. Chu;R. L. Kashyap
Affiliations:
Knowledge-Based Systems Lab., School of Electrical Engineering, Purdue University, West Lafayette, Indiana;School of Industrial Engineering, Purdue University, West Lafayette, Indiana;Knowledge-Based Systems Lab., School of Electrical Engineering, Purdue University, West Lafayette, Indiana
Venue:
IEA/AIE '90 Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1
Year:
1990

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Abstract

A formalism for symbolic representation of three-dimensional model and its use for knowledge representation and control structure are presented. A robust feature-based design (RFBD) approach has been developed to represent three dimensional objects and to provide meaningful geometric and topological properties for manufacturability evaluation. For knowledge acquisition, binary syntactic primitive pairs have been established for high level symbolic reasoning. Symbolic reasoning tables provide five stages for proper knowledge invocation. This framework enables the system to reason about geometric shape based on syntactic pattern primitives and not on features. Both production rule systems and frames are used to represent the declarative and procedural knowledge sources in the EXCAST-1.0 (the expert system). Automatic meta-rule formation is proposed as a part of knowledge refinement process and the semantic data model is also proposed to aid various CAM applications for use in RFBD. The implementation of the algorithms and examples are provided.