Practical Implementation of Robust Design Assisted by Response Surface Approximation and Visual Data-Mining
Practical Implementation of Robust Design Assisted by Response Surface Approximation and Visual Data-Mining
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DOI：
10.1115/1.3125207
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发表时间：
2009-06
影响因子：
3.3
通讯作者：
K. Shimoyama;J. Lim;Shinkyu Jeong;S. Obayashi;M. Koishi
中科院分区：
文献类型：
--
作者：
K. Shimoyama;J. Lim;Shinkyu Jeong;S. Obayashi;M. Koishi
提出了一种多目标稳健设计优化的新方法，并将其应用于一个具有大量目标函数的实际设计问题。该方法借助响应面近似和可视化数据挖掘，在计算时间和数据解释方面取得了两大成果。用于响应面近似的克里金模型可以显著减少稳健性预测的计算时间。此外，使用自组织映射作为一种数据挖掘技术，可以以一种易于理解的二维形式可视化最优性和稳健性之间复杂的设计信息。因此，可以全面地提取和解释设计的最优性和稳健性之间的权衡关系，以及确定设计空间中的最佳点位置。
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.