Design Space Analysis with Hyperdimensional Metamodels

Colorado School Of Mines, Golden CO

Investigators

Abstract

The research objective of this award is to develop methods that enable the product design space to be modeled so that promising regions can be identified and developed. Every product has a design space associated with the choices made during design. Often, these choices are made with limited or changing information and thus the resulting design may not lie in the best region of the design space. By modeling the design space, information about design tradeoffs and opportunities for technological innovation can be identified and used to improve the design of the product. This research focuses on the tasks of accurately modeling the design space with available data, recognizing the regions within the design space that contain the most promising designs, and applying multi-objective optimization techniques to select the best designs from these regions. Deliverables include the development of algorithms to support adaptive data collection and the handling of data from multiple sources, methods that characterize and can identify promising regions within the design space, and the integration of optimization methods within a software system that supports multi-objective optimization problems. If successful, the results of this research will provide opportunities to dramatically reduce the time it takes to design a new product while improving the quality of product designs developed with these methods. These methods will be general enough to be applied to a wide range of product design problems. Results from this research will be widely disseminated through professional meetings and conferences and through publication in disciplinary journals. Collaborations with industrial partners to evaluate these methods on real-world problems are anticipated and the undergraduate and graduate students involved in the project will benefit from their exposure to an emerging design technology.