scholarly journals Real-World Application of Robust Design Optimization Assisted by Response Surface Approximation and Visual Data-Mining

2009 ◽  
Vol 24 ◽  
pp. 13-24
Author(s):  
Koji Shimoyama ◽  
Shinkyu Jeong ◽  
Shigeru Obayashi
Keyword(s):  
Data Mining ◽  
Design Optimization ◽  
Response Surface ◽  
Robust Design ◽  
Real World ◽  
Robust Design Optimization ◽  
Visual Data ◽  
Visual Data Mining ◽  
Response Surface Approximation ◽  
Real World Application

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

2009 ◽  
Vol 131 (6) ◽  
Author(s):  
Koji Shimoyama ◽  
Jin Ne Lim ◽  
Shinkyu Jeong ◽  
Shigeru Obayashi ◽  
Masataka Koishi
Keyword(s):  
Data Mining ◽  
Response Surface ◽  
Robust Design ◽  
Robust Design Optimization ◽  
Computational Time ◽  
Practical Implementation ◽  
Visual Data ◽  
Visual Data Mining ◽  
Response Surface Approximation ◽  
Surface Approximation

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.

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