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Our research is motivated by the need for a rigorous engineering design framework and the need for developing a demand analysis approach that is critical for assessing the profit a product can bring. A Decision-Based Design framework is presented as a rigorous design approach and the method of Discrete Choice Analysis is applied in order to create a demand model that facilitates engineering decision-making in vehicle design with an emphasis on engine design. Through interdisciplinary collaborations, we illustrate how the gap between market research and engineering analysis can be bridged in product design.

To address the conflicting goals of minimal piston friction and minimal piston noise, a dynamic power cylinder model was developed to predict piston motion and side loads within the cylinder. This correlated model was the basis of a comprehensive analytical design of experiments (DOE) where both piston noise and piston friction were monitored. The results of the DOE were used to generate metamodels for piston friction and for piston noise. To insure design robustness, variability was introduced into the surrogate models via First Order Reliability Method (FORM). A Pareto curve using 99% probability was constructed and a piston robust to both noise and friction was selected.