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dc.contributor.authorRecuk, Stephen Joseph
dc.contributor.authorAughenbaugh, Jason Matthew
dc.contributor.authorBruns, Morgan Chase
dc.contributor.authorParedis, Chris
dc.date.accessioned2010-06-18T20:37:25Z
dc.date.available2010-06-18T20:37:25Z
dc.date.issued2006
dc.identifier.citationRekuc, S. J., Aughenbaugh, J. M., Bruns, M. and Paredis, C. J. J. (2006) "Eliminating Design Alternatives based on Imprecise Information." in Proceedings of the SAE 2006 World Congress. Paper No. 2006-01-0272.en_US
dc.identifier.isbn9780768017670
dc.identifier.issn0099-5908
dc.identifier.urihttp://hdl.handle.net/1853/34047
dc.descriptionThis paper was presented at the SAE 2006 World Congress, 2006. Reprinted with permission from SAE paper 2006-01-0272 © 2006 SAE International.en_US
dc.description.abstractIn this paper, the relationship between uncertainty and sets of alternatives in engineering design is investigated. In sequential decision making, each decision alternative actually consists of a set of design alternatives. Consequently, the decision-maker can express his or her preferences only imprecisely as a range of expected utilities for each decision alternative. In addition, the performance of each design alternative can be characterized only imprecisely due to uncertainty from limited data, modeling assumptions, and numerical methods. The approach presented in this paper recognizes the presence of both imprecision and sets in the design process by focusing on incrementally eliminating decision alternatives until a small set of solutions remains. This is a fundamental shift from the current paradigm where the focus is on selecting a single decision alternative in each design decision. To make this approach economically feasible, one needs efficient methods for eliminating alternatives—that is, methods that eliminate as many alternatives as possible given the available imprecise information. Efficient elimination requires that one account for dependencies between uncertain quantities, such as shared uncertain variables. In this paper, criteria for elimination with and without shared uncertainty are presented and compared. The set-based nature of design and the presence of imprecision are introduced, elimination criteria are discussed, and the overall set-based approach and elimination criteria are demonstrated with the design of a gearbox as an example problem.en_US
dc.description.sponsorshipNASA Ames Research Centeren_US
dc.description.sponsorshipNational Science Foundation (Grant #DMI-0522116)
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectDecision makingen_US
dc.subjectGearboxen_US
dc.subjectProcess of eliminationen_US
dc.subjectImprecisionen_US
dc.titleEliminating Design Alternatives Based on Imprecise Informationen_US
dc.typePaperen_US
dc.typeProceedingsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. The Systems Realization Laboratory
dc.publisher.originalSociety for Automotive Engineers International


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