Intelligent Framework for Part Design

Article type: Research Article

Authors: Hambaba, M. | Elsherif, H. | O'Brien, W. | Bergstrom, E.

Affiliations: Intelligent Systems Laboratory, Stevens Institute of Technology, Hoboken, New Jersey 07030

Abstract: A framework for using artificial neural networks to design injection molded parts is presented. This framework can be achieved through two approaches. The first approach uses a mapping technique to represent the design knowledge into an artificial neural network. This mapping approach is used in a distributed way to encode the design knowledge. The second approach uses an intelligent hybrid system that integrates the knowledge-base (expert) system and the neural networks together into one combined system. This tightly coupled intelligent system takes the benefits of the expert system and the neural networks and combines them to eliminate the limitations of each. Working design examples of these two implemented approaches will be explored. The concepts to be incorporated in future implementations will be mentioned.

DOI: 10.3233/IFS-1994-2107

Journal: Journal of Intelligent and Fuzzy Systems, vol. 2, no. 1, pp. 89-97, 1994