Abstract
Reliability Based Design Optimization(RBDO) is a topic of interest for research in both academia and industry. RBDO yields the ability not only to efficiently design a product, but to incorporate the statistical distributions of the design variables to estimate and even control the product’s reliability. RBDO typically involves adjusting the mean values of the design variables while fixing the spread parameters, often measured as variance, in order to accomplish a given objective within the stated constraints. However, often times in manufacturing, to completely redesign a component requires a huge amount of financial resources needed for accommodating these radical design changes. This paper proposes an alternate way to meet given design criteria by fixing the mean values of the statistical inputs and allowing the spread parameters to become design variables. By performing this type of optimization, the design changes are kept to a minimum, and the focus is instead shifted to variance control. These optimizations can then relate to the designer which variance variables can be allowed to expand and which variance variables need to be reduced in order to meet given design constraints. An initial study is performed on a three-bar truss subject to static loading with material variability. A more complex example is performed involving the cost minimization of an Unmanned Undersea Vehicle subjected to hydrostatic buckling.
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