Fuzzy Reliability-Based Optimization for Engineering System Design

Both the performance and the useful life of engineering systems can be affected by uncertainties that have not been considered at the design stage of such systems. Therefore, uncertainty, reliability, and robustness analyses are important tools to evaluate the influence of uncertainties on the operational conditions of machines and structures during the design process. In this contribution, a fuzzy reliability-based optimization procedure is presented. This methodology is based on the fuzzy logic approach and considers both the possibility and fuzzy states assumptions, in which the uncertain parameters are modeled as fuzzy variables. Thus, the associated optimization problems are solved through a nested algorithm. An inner optimization loop is used to obtain the limits of the uncertain variables, and an outer optimization loop evaluates a predefined fuzzy reliability index within the previously obtained bounds. The performance of the proposed approach was evaluated through a benchmark function and two engineering design problems. The reliability fuzzy approach is compared with another existing strategy. The obtained results demonstrate that the proposed approach represents a new alternative to reliability-based design of engineering systems, eliminating the influence of the probability and/or possibility distributions on the obtained results.