Multiobjective optimization design methodology for incorporating manufacturing uncertainties in advanced composite structures

A methodology is proposed herein which incorporates manufacturing uncertainties into a multiobjective optimal design algorithm for structures fabricated with fibrous composite laminated materials. Every single objective function for this class of stochastic multiobjective optimization problems and the corresponding probabilistic constraints are transformed into equivalent deterministic quantities using chance constrained programming, and then fuzzy set theory is employed as the assistant of decision making to solve a multiobjective optimization problem to get the best compromise solution. A finite element model of a single-link flexible laminated fibrous composite robot arm including the effects of damping and hub inertia demonstrates the significance of employing the proposed methodology for obtaining the high performance characteristics of composite structures with random parameters. The random parameters employed in this example for the fabrication of the composite robot arm are ply thickness, fiber orientation, and fiber volume fraction.