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Decision making is necessary to provide a synthesis scheme to design activities and devise the most preferred design alternative.  Decisions made for multiple interdependent design objectives can increase complexity and uncertainty throughout the design process.  To address this issue a new method will be proposed for incorporating the modeling of designer preferences and trade-offs using Multi-Attribute Utility Theory (MAUT) and Conjoint Analysis in simulation-based design under the consideration of uncertainty.  To aid the use of reliability-based design as a decision-making tool, a new probabilistic analysis tool, namely a stochastic local regression, will be introduced.  The inclusion of a stochastic local regression method will replace the use of a physical model allowing for a drastic decrease in computational cost with sufficient accuracy. The efficacy and application of the proposed framework will be demonstrated with the design of a power-generating shock absorber

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Master of Science Thesis

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