Collaborative design optimization based on knowledge discovery from simulation

Authors:
Jie Hu;Yinghong Peng
Affiliations:
Institute of Knowledge Based Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China;Institute of Knowledge Based Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, P.R. China
Venue:
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Year:
2006

Citing 4
Cited 0

Combining process planning and concurrent engineering to support printed circuit board assembly

Computers and Industrial Engineering - Collection of papers on Computer-Integrated Manufacturing
Data Mining for Design and Manufacturing: Methods and Applications

Data Mining for Design and Manufacturing: Methods and Applications
Data Mining for Scientific and Engineering Applications

Data Mining for Scientific and Engineering Applications
WebBlow: a Web/agent-based multidisciplinary design optimization environment

Computers in Industry - Special issue: Knowledge sharing in collaborative design environments

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a method of collaborative design optimization based on knowledge discovery. Firstly, a knowledge discovery approach based on simulation data is presented. Rules are extracted by knowledge discovery algorithm, and each rule is divided into several intervals. Secondly, a collaborative optimization model is established. In the model, the consistency intervals are derived from intervals of knowledge discovery. The model is resolved by genetic arithmetic. Finally, The method is demonstrated by a parameter design problem of piston-connecting mechanism of automotive engine. The proposed method can improve the robustness of collaborative design optimization.