Inspired by work on allocating risk between the different components of a system for a minimal cost, we explore the optimal allocation of uncertainty in a single component. The tradeoffs of uncertainty reduction measures on the weight of structures designed for reliability are explored. The uncertainties in the problem are broadly classified as error and variability. Probabilistic design is carried out to analyze the effect of reducing error and variability on the weight. As a demonstration problem, the design of composite laminates at cryogenic temperatures is chosen because the design is sensitive to uncertainties. For illustration, variability reduction takes the form of quality control, while error is reduced by including the effect of chemical shrinkage in the analysis. Tradeoff plots of uncertainty reduction measures, probability of failure and weight are generated that could allow choice of optimal uncertainty control measure combination to reach a target probability of failure with minimum cost. In addition, the paper also compares response surface approximations to direct approximation of a probability distribution for efficient estimation of reliability.
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