An Engineering Decision Support System (EDSS) with alternative-criterion pair evaluations Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/ks65hg27c

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  • An Engineering Decision Support System, EDSS, was developed using Bayesian mathematics which incorporates knowledge and confidence components observed in alternative-criterion pair decision making. The separation of knowledge and confidence has been previously unaccounted for in decision-making methods. EDSS provides decision support to individuals or teams which must make choices between alternatives using alternative-criterion pair evaluations. Further, EDSS was instanciated into computer software. The EDSS decision support system was statistically tested using two variables, mechanical experience of the participants and the use of a decision method, at two different levels and in a replicated factorial experiment. The experiment consisted of teams of subjects solving a simple mechanical design problem. Data from the experiment was collected for eighteen different metrics in four categories. This research reports on each of eighteen metrics using the hypothesis that the use of EDSS will show improvements in, or positive impact on, the following four categories: the decision making productivity of idea processing, the decision-making process, the perception of the decisions made by the decision makers, and the ease of use of a computer decision support tool. Statistical results of the experiment showed that EDSS successfully matched ad-hoc and Pugh's decision matrix performance for sixteen of the eighteen metrics and statistically exceeded the remaining two. These two metrics are, the conduction of more evaluations of alternative-criterion pairs ,and increased problem understanding. This research also shows that a new alternative-criterion pair evaluation method has been successfully created that provides for: - A separation of knowledge and confidence in the Belief Model of decision making. - Decision results without complete evaluation of all alternative-criterion pairs. - Aggregation of preferences from team members. - A convenient means for investigating decision improvements.
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