Fuzzy neural networks for intelligent design retrieval using associative manufacturing features |
| |
Authors: | Chieh-Yuan Tsai C. Alec Chang |
| |
Affiliation: | (1) Department of Industrial Engineering and Management, Yuan-Ze University, 135 Yuan-Tung Rd., Chung-Li, Taoyuan, 320, Taiwan;(2) Department of Industrial and Manufacturing System Engineering, E3437G Engineering Building East, University of Missouri—Columbia, Columbia, MO 65211, USA |
| |
Abstract: | In the conceptual design stage, designers usually initiate a design concept through an association activity. The activity helps designers collect and retrieve reference information regarding a current design subject instead of starting from scratch. By modifying previous designs, designers can create a new design in a much shorter time. To computerize this process, this paper proposes an intelligent design retrieval system involving soft computing techniques for both feature and object association functions. A feature association method that utilizes fuzzy relation and fuzzy composition is developed to increase the searching spectrum. In the mean time, object association functions composed by a fuzzy neural network allow designers to control the similarity of retrieved designs. Our implementation result shows that the intelligent design retrieval system with two soft computing based association functions can retrieve target reference designs as expected. |
| |
Keywords: | Soft computing fuzzy set theory neural networks manufacturing features and intelligent design retrieval |
本文献已被 SpringerLink 等数据库收录! |
|