Journal of Northeastern University Natural Science ›› 2015, Vol. 36 ›› Issue (6): 908-912.DOI: 10.12068/j.issn.1005-3026.2015.06.032

• Management Science • Previous Articles    

Case-based Fast Optimization Design for Complex Products

FENG Guo-qi1, CUI Dong-liang2, MA Ming-xu3   

  1. 1. School of Business Administration, Northeastern University, Shenyang 110819, China; 2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China; 3. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China.
  • Received:2014-04-30 Revised:2014-04-30 Online:2015-06-15 Published:2015-06-11
  • Contact: FENG Guo-qi
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Abstract: Optimization design for complex products is of great difficulty because of its multidisciplinary characteristics. Multidisciplinary design optimization (MDO) can better deal with this issue, but there are still some flaws in implementing this technology. The exploration of the laws from previous cases can enhance the efficiency and quality of product design. Unlike the traditional methods of MDO, a fast design optimization is proposed from the perspective of knowledge application. Based on the key parameters extracted from design versions, the weights of vector are acquired by the calculation of the relationship between input parameters and output parameters. Rapid clustering is performed based on expert experience and design objectives, parameters are designed by the extension and re-sampling of cluster members, experiments are designed to provide high-quality initial solutions to the optimization designs with computational constraint, and the other samples from the same cluster are given knowledge-based evaluation and simulated with fast sampling optimization scheme. The results showed that this method is of great effectiveness and feasibility.

Key words: complex product, design knowledge, optimization design, weighted clustering

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