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dc.contributor.authorSelva, Daniel
dc.contributor.authorCrawley, Edward F.
dc.contributor.authorCameron, Bruce Gregory
dc.date.accessioned2015-05-07T12:42:37Z
dc.date.available2015-05-07T12:42:37Z
dc.date.issued2014-06
dc.date.submitted2014-05
dc.identifier.issn0934-9839
dc.identifier.issn1435-6066
dc.identifier.urihttp://hdl.handle.net/1721.1/96923
dc.description.abstractDespite the development of a variety of decision-aid tools for assessing the value of a conceptual design, humans continue to play a dominant role in this process. Researchers have identified two major challenges to automation, namely the subjectivity of value and the existence of multiple and conflicting customer needs. A third challenge is however arising as the amount of data (e.g., expert judgment, requirements, and engineering models) required to assess value increases. This brings two challenges. First, it becomes harder to modify existing knowledge or add new knowledge into the knowledge base. Second, it becomes harder to trace the results provided by the tool back to the design variables and model parameters. Current tools lack the scalability and traceability required to tackle these knowledge-intensive design evaluation problems. This work proposes a traceable and scalable rule-based architecture evaluation tool called VASSAR that is especially tailored to tackle knowledge-intensive problems that can be formulated as configuration design problems, which is demonstrated using the conceptual design task for a laptop. The methodology has three main steps. First, facts containing the capabilities and performance of different architectures are computed using rules containing physical and logical models. Second, capabilities are compared with requirements to assess satisfaction of each requirement. Third, requirement satisfaction is aggregated to yield a manageable number of metrics. An explanation facility keeps track of the value chain all along this process. This paper describes the methodology in detail and discusses in particular different implementations of preference functions as logical rules. A full-scale example around the design of Earth observing satellites is presented.en_US
dc.language.isoen_US
dc.publisherSpringer-Verlagen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s00163-014-0180-xen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleA rule-based method for scalable and traceable evaluation of system architecturesen_US
dc.typeArticleen_US
dc.identifier.citationSelva, Daniel, Bruce Cameron, and Edward F. Crawley. “A Rule-Based Method for Scalable and Traceable Evaluation of System Architectures.” Research in Engineering Design 25, no. 4 (June 12, 2014): 325–349.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Divisionen_US
dc.contributor.mitauthorSelva, Danielen_US
dc.contributor.mitauthorCameron, Bruce Gregoryen_US
dc.contributor.mitauthorCrawley, Edward F.en_US
dc.relation.journalResearch in Engineering Designen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsSelva, Daniel; Cameron, Bruce; Crawley, Edward F.en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-7618-5182
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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