A multi-disciplinary modeling and design optimization formulation for uncertainty effects consideration is presented in this paper. The optimization approach considers minimization of uncertainty factors related to the overall system performance while satisfying target requirements specified in the form of constraints. The design problem is decomposed into two analysis systems; performance design and uncertainty effects analysis. Each design system can be partitioned into several subsystems according to the different functions they perform. Performance evaluation is considered by minimizing the variations between specified expected values of performance functions and their target values. Uncertainty effects analysis is defined by minimizing the ratio of the maximum variations caused by uncertainty factors over the expected function values. The entire problem has been treated as a multi-disciplinary design optimization (MDO) for maximum robustness and performance achievement. An electromechanical system is used as an example to demonstrate this optimization methodology.

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