*In this study, following the concept of set-based design, after preparing global calculation results, we introduced the approach of setting the design solution area that satisfies the product performance goals of the system design. In this approach, from the viewpoint of considering uncertainty, we aimed to develop an analysis method that can get the organic relationship between target variables and design variables. And more, under the assumption that it is difficult to comprehend the full picture of products that are becoming more sophisticated and complex with the knowledge that has been fostered by skilled engineers, the proposed system uses the objective calculation indices that is provided knowledge of the designer. Specifically, the following method are proposed to solve the problem.*

*- Implementation of meta-modeling of design space.*

*- Classified solution space using a density-based clustering method to detect that the solution spaces are divided into multiple disconnected space.*

*- Defined an index called distribution concentration and expressed the possibility of dealing with the uncertainty of the solution domain.*

*- The network diagram based on the calculated index values was proposed to confirm the change in the characteristics of the solution space when the performance target of the product was changed.*

*Finally, the effectiveness of the proposed method was verified by applying it to actual simulation results.*

　Based on the verification of the results obtained using the proposed method, the divided solution regions were distinguished by clustering, and the changes in the solution space due to the variations in the constraints were visualized using network representation. Moreover, the problems related to experimental design were solved using metamodeling. In addition, the separation of the global computation and solution search processes solved the issues listed in the previous rsearch. The proposed method therefore provides an overview of the design space, which includes the discretization of the solution space and quantitative evaluation of the constraints. In addition, the indices and clustering method proposed in this study are effective, although they require further improvements.


Design Space Analysis Method for Support of System Design Under the Consideration of Uncertainties in the Early Design Stage

Division / Sponsors: 
Design Engineering Division and Computers & Information In Engineering Division


Paper Proceedings: https://asmedigitalcollection.asme.org/IDETC-CIE/IDETC-CIE2020/volume/83907

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