EVALUATING CLUSTERING ALGORITHMS TO IDENTIFY SUBPROBLEMS IN DESIGN PROCESSES

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dc.contributor.advisorHerrmann, Jeffrey Wen_US
dc.contributor.authorMorency, Michael Johnen_US
dc.contributor.departmentSystems Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2017-06-22T06:44:18Z
dc.date.available2017-06-22T06:44:18Z
dc.date.issued2017en_US
dc.description.abstractDesign problems are inherently intricate and require multiple dependent decisions. Because of these characteristics, design teams generally choose to decompose the main problem into manageable subproblems. This thesis describes the results of a study designed to (a) explore clustering algorithms as a new and repeatable way to identify subproblems in recorded design team discussions, (b) assess the quality of the identified subproblems, and (c) examine any relationships between the subproblems and final design or team experience level. We observed five teams of public health professionals and four teams of undergraduate students and applied four clustering algorithms to identify the team’s subproblems and achieve the aforementioned research goals. The use of clustering algorithms to identify subproblems has not been documented before, and clustering presents a repeatable and objective method for determining a team’s subproblems. The results from these algorithms as well as metrics noting the each result’s quality were captured for all teams. We learned that each clustering algorithm has strengths and weaknesses depending on how the team discussed the problem, but the algorithms always accurately identify at least some of the discussed subproblems. Studying these identified subproblems reveals a team’s design process and provides insight into their final design choices.en_US
dc.identifierhttps://doi.org/10.13016/M29C54
dc.identifier.urihttp://hdl.handle.net/1903/19567
dc.language.isoenen_US
dc.subject.pqcontrolledOperations researchen_US
dc.subject.pquncontrolledalgorithmsen_US
dc.subject.pquncontrolledclusteringen_US
dc.subject.pquncontrolleddesignen_US
dc.subject.pquncontrolledPODen_US
dc.subject.pquncontrolledsubproblemsen_US
dc.titleEVALUATING CLUSTERING ALGORITHMS TO IDENTIFY SUBPROBLEMS IN DESIGN PROCESSESen_US
dc.typeThesisen_US

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