A nested extreme response surface approach for reliability based product design

A primary concern in product design is ensuring high reliability throughout a product life-cycle subject to timevariant operating conditions and component deterioration. This paper presents a nested extreme response surface (NERS) approach to efficiently carry out time-dependent reliability analysis and determine the optimal designs. The NERS employs kriging model to build a nested response surface of time corresponding to the extreme value of the limit state function. The efficient global optimization techniqe is integrated with the NERS to extract the extreme time responses of the limit state function for any given system design. An adaptive response prediction and model maturation mechanism is developed based on mean square error (MSE) to concurrently improve the accuracy and computational efficiency of the proposed approach. With the nested response surface of time, the time-dependent reliability analysis can be converted into the time-independent reliability analysis and existing advanced reliability analysis and design methods can be used. The NERS is integrated with reliability-based product design optimization with time-dependent probabilistic constraints. One case study is used to demonstrate the efficacy of the proposed NERS approach.