{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/86444"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/86444","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Intelligent Group Structuring for Mass Collaboration within Engineering Design","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Ball, Zachary; 0000-0002-1378-0531"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Lewis, Kemper","Mechanical and Aerospace Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-02-21T17:22:30Z","date_published":"2025-02-21T17:22:30Z","updated_at":"2026-07-27T19:05:32Z","subjects":["mechanical engineering"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/86444","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Lewis, Kemper","Mechanical and Aerospace Engineering"]},{"key":"dc:creator","label":"Author","values":["Ball, Zachary; 0000-0002-1378-0531"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-02-21T17:22:30Z","2020"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["mechanical engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/86444"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","Collective reasoning is an inherent trait in human behavior as a means to advance society. This behavior is exemplified in mass collaboration within the design engineering process as it supports the inclusion of unique perspectives when working on complex problems. Increasing the number of individuals providing input and support into design challenges can increase innovation, decrease product development times and provide solutions that truly encompass the needs of the market. Along with these benefits, many challenges arise to fully capitalize on the collective efforts of individuals. One of the greatest challenges in applying mass collaboration to the engineering of solutions is the organization of individuals within large design efforts. This dissertation approaches the problem of organization with a continually narrowing level of detail. To begin, a top-level overview of a simulated design process is studied with a primary focus being placed on the network structure of interconnected groups. Next, the scope is narrowed by transitioning the focal point to simulated groups of multi-disciplinary engineers. Two frameworks are developed focusing on the optimal network structure of groups with respect to their communication trends, and the recommendation of individuals for projects to which the impact of their efforts would be maximized. Finally, the scope is tightened once more, as both individuals and design challenges are studied for their competency distribution and semantic makeup, allowing for more accurate and rigorous adhesion to optimal design network structural requirements.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Intelligent Group Structuring for Mass Collaboration within Engineering Design"]}]}],"canonical_facts":{"dc:contributor":["Lewis, Kemper","Mechanical and Aerospace Engineering"],"dc:creator":["Ball, Zachary; 0000-0002-1378-0531"],"dc:date":["2025-02-21T17:22:30Z","2020"],"dc:description":["Ph.D.","Collective reasoning is an inherent trait in human behavior as a means to advance society. This behavior is exemplified in mass collaboration within the design engineering process as it supports the inclusion of unique perspectives when working on complex problems. Increasing the number of individuals providing input and support into design challenges can increase innovation, decrease product development times and provide solutions that truly encompass the needs of the market. Along with these benefits, many challenges arise to fully capitalize on the collective efforts of individuals. One of the greatest challenges in applying mass collaboration to the engineering of solutions is the organization of individuals within large design efforts. This dissertation approaches the problem of organization with a continually narrowing level of detail. To begin, a top-level overview of a simulated design process is studied with a primary focus being placed on the network structure of interconnected groups. Next, the scope is narrowed by transitioning the focal point to simulated groups of multi-disciplinary engineers. Two frameworks are developed focusing on the optimal network structure of groups with respect to their communication trends, and the recommendation of individuals for projects to which the impact of their efforts would be maximized. Finally, the scope is tightened once more, as both individuals and design challenges are studied for their competency distribution and semantic makeup, allowing for more accurate and rigorous adhesion to optimal design network structural requirements.","**To request an accessible version of the file(s) associated with this item, contact library@buffalo.edu. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/86444"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["mechanical engineering"],"dc:title":["Intelligent Group Structuring for Mass Collaboration within Engineering Design"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:32Z"}