Practical Implementation of Robust Design Assisted by Response Surface Approximation and Visual Data-Mining

Author:

Shimoyama Koji1,Lim Jin Ne1,Jeong Shinkyu1,Obayashi Shigeru1,Koishi Masataka2

Affiliation:

1. Institute of Fluid Science, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan

2. CAE Laboratory, Yokohama Rubber Co., Ltd., 2-1 Oiwake, Hiratsuka, Kanagawa 254-8601, Japan

Abstract

A new approach for multi-objective robust design optimization was proposed and applied to a practical design problem with a large number of objective functions. The present approach is assisted by response surface approximation and visual data-mining, and resulted in two major gains regarding computational time and data interpretation. The Kriging model for response surface approximation can markedly reduce the computational time for predictions of robustness. In addition, the use of self-organizing maps as a data-mining technique allows visualization of complicated design information between optimality and robustness in a comprehensible two-dimensional form. Therefore, the extraction and interpretation of trade-off relationships between optimality and robustness of design, and also the location of sweet spots in the design space, can be performed in a comprehensive manner.

Publisher

ASME International

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials

Reference30 articles.

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