In deterministic optimization, engineering designs are often driven to the limits of the design constraints, leaving little or no latitude for tolerances in modeling and simulation uncertainties and/or manufacturing process variability. Optimized designs determined without due consideration of tolerances can be unreliable leading to catastrophic failure. CCAD's research in this area is focused on the investigation and development of new reliability-based design optimization (RBDO) methods and software systems that enable the determination of optimum designs that incorporate confidence ranges for mechanical component/system and electronic assembly. Specific research thrusts include the development of uncertainty modeling, reliability sensitivity analysis, and generalized RBDO methods.

To address the sensitivity of some manufacturing processes, for example metal stamping and forming, and fatigue life estimation techniques to material property uncertainty, empirical fatigue modeling, external load variability, and dynamic stresses and strains, the Center has adopted an exacting approach to achieve robust RBDO methods and applications. The methodologies developed at CCAD are, however, applicable to general RBDO problems, as a result of an adaptive probabilistic constraint evaluation strategy employed in RBDO research efforts. By integrating system probability analysis with the unified system space in the design optimization process, a design potential method (DPM) has been developed for highly effective probabilistic constraint approximation. The use of the DPM method significantly improves the RBDO convergence rate since it applies important design information obtained during reliability analysis for probabilistic constraint evaluation.