Seepersad, Carolyn C.2011-02-092011-02-092017-05-112011-02-092011-02-092017-05-112010-12December 2http://hdl.handle.net/2152/ETD-UT-2010-12-2333textFor many products, the design process is a complex system involving the interaction of many distributed design activities that need to be carefully coordinated. This research develops a new tool, called a Bayesian network classifier, to improve one specific aspect of this challenge: quantitatively capturing a consensus of which designs are feasible options for meeting system-wide engineering requirements. Classifiers enable designers to independently develop and share maps of the feasible regions of their design space, enabling set-based collaborative design. The method is set-based in that resources are used to thoroughly understand design tradeoffs before commitment is made to a final design. The method is collaborative because the maps are coordinated between design teams to represent the mutually feasible design space of all stake-holders. The benefits are a more thorough understanding of the system-wide design problem across team boundaries as well as knowledge capture for future re-use, potentially leading to faster product development and higher quality products.application/pdfengSet-based designCollaborative designMultidisciplinary designDistributed designVertical couplingthesis2011-02-09