Belief reliability-based design optimization method with quantile index under epistemic uncertainty

Product reliability design optimization is affected by epistemic uncertainty greatly, which leaves significant risks in product use. In this paper, a new belief reliability-based design optimization (BRBDO) method under epistemic uncertainty is established to handle this problem. First, the belief reliability theory is introduced into the design optimization problem, and a quantile index is proposed to quantify belief reliability level based on uncertainty theory, through which a rapid analysis method called first order belief reliability analysis (FOBRA) method is developed. Then, according to the different trade-off strategies, two types of design optimization models are established, and corresponding FOBRA-based computation methods are also demonstrated. Finally, several case applications are studied to verify the effectiveness of the analysis and design optimization methods proposed in this paper. The results indicate that the BRODO method with the quantile index can save a lot of computational time with acceptable accuracy and can rationally cope with epistemic uncertainty.

Automated summary

In this paper, a new belief reliability-based design optimization (BRBDO) method is established to handle the impact of epistemic uncertainty on product reliability design optimization. A quantile index is proposed to quantify belief reliability level based on uncertainty theory, and a rapid analysis method called first order belief reliability analysis (FOBRA) is developed. Two types of design optimization models are established according to different trade-off strategies, and corresponding FOBRA-based computation methods are also demonstrated. Several case applications are conducted to verify the effectiveness of the proposed analysis and design optimization methods.