Designers and design researchers both agree that developing many feasible alternatives at the conceptual design stage is useful. In this paper we introduce generative configuration design (GCD) for conceptual design. We provide a partition of knowledge accessed during GCD and use the partitioned knowledge foundation to compare design tool architectures so that computational improvements can be made. We present an improved architecture for a GCD algorithm and implement it as a tool for office chair design. Subsequent examples show tradeoffs between computational load and design variety when applying constraints for behavior testing.
- Design Engineering Division and Computers and Information in Engineering Division
Partitioning Knowledge for Generative Configuration Design
- Views Icon Views
- Share Icon Share
- Search Site
Shi, H, & Schmidt, L. "Partitioning Knowledge for Generative Configuration Design." Proceedings of the ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3b: 15th International Conference on Design Theory and Methodology. Chicago, Illinois, USA. September 2–6, 2003. pp. 909-917. ASME. https://doi.org/10.1115/DETC2003/DTM-48686
Download citation file: