Integrated parameter and tolerance optimization of a centrifugal compressor based on a complex simulator

Han, Mei; Liu, Xuejun; Huang, Min; Tan, Matthias Hwai Yong

doi:10.1080/00224065.2019.1611358

Cited by 10 publications

(1 citation statement)

References 18 publications

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“…GP models have successful applications in various research fields, such as statistical process control and advanced manufacturing processes. 35,36 As a nonparametric model, GP can accurately estimate the relationship models from experimental data without prior information. 21 There are two given × 1 vectors for output responses = ( 1 , … , ) and input variables = ( 1 , … , ) .…”

Section: Gp Modelmentioning

confidence: 99%

Life‐cycle reliability‐based robust design optimization for GP model with response uncertainty

Feng

Wang

et al. 2021

Quality & Reliability Eng

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Reliability-based robust design optimization (RBRDO) is a crucial tool for lifecycle quality improvement. Gaussian process (GP) model is an effective alternative modeling technique that is widely used in robust parameter design. However, there are few studies to deal with reliability-based design problems by using GP model. This article proposes a novel life-cycle RBRDO approach concerning response uncertainty under the framework of GP modeling technique. First, the hyperparameters of GP model are estimated by using the Gibbs sampling procedure. Second, the expected partial derivative expression is derived based on GP modeling technique. Moreover, a novel failure risk cost function is constructed to assess the life-cycle reliability. Then, the quality loss function and confidence interval are constructed by simulated outputs to evaluate the robustness of optimal settings and response uncertainty, respectively. Finally, an optimization model integrating failure risk cost function, quality loss function, and confidence interval analysis approach is constructed to find reasonable optimal input settings. Two case studies are given to illustrate the performance of the proposed approach. The results show that the proposed approach can make better trade-offs between the quality characteristics and reliability requirements by considering response uncertainty.

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Section: Gp Modelmentioning

confidence: 99%