The study of a knowledge-based constraints network system (KCNS) for concurrent engineering

Authors:
Wei-ming Wang;Jie Hu;Fei Zhou;Da-yong Li;Xiang-jun Fu;Ying-hong Peng
Affiliations:
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
Venue:
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Year:
2005

Citing 2
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Robust design based on constraint networks

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Abstract

This research article demonstrates the use of a constraints network for modeling the knowledge which is necessary for concurrent product design. A Knowledge-based Constraints Network System (KCNS) has been developed to maintain design consistency and to support the selection of appropriate design parameter intervals. A data-mining algorithm named fuzzy-rough algorithm is developed to acquire the knowledge level constraints from the numerical simulation. The method integrated Case Based Reasoning (CBR) and Rule Based Reasoning (RBR) with interval consistency algorithm is adopted to predict the potential conflicts and to specify the interval of design parameters. The design example of a crank connecting link in a V6 engine shows the validity of the system.