Uncertain Random Optimization Models Based on System Reliability

Authors

Qinqin Xu, Yuanguo Zhu^*,

School of Science, Nanjing University of Science and Technology, Nanjing, Jiangsu, 210094, China

^*Corresponding author. Email: ygzhu@njust.edu.cn

DOI

10.2991/ijcis.d.200915.002How to use a DOI?

Keywords

Optimization model; Chance theory; Belief reliability; Hard failure; Soft failure; Jet pipe servo valve

Abstract

The reliability of a dynamic system is not constant under uncertain random environments due to the interaction of internal and external factors. The existing researches have shown that some complex systems may suffer from dependent failure processes which arising from hard failure and soft failure. In this paper, we will study the reliability of a dynamic system where the hard failure is caused by random shocks which are driven by a compound Poisson process, and soft failure occurs when total degradation processes, including uncertain degradation process and abrupt degradation shifts caused by shocks, reach a predetermined critical value. Two types of uncertain random optimization models are proposed to improve system reliability where belief reliability index is defined by chance distribution. Then the uncertain random optimization models are transformed into their equivalent deterministic forms on the basis of α-path, and the optimal solutions may be obtained with the aid of corresponding nonlinear optimization algorithms. A numerical example about a jet pipe servo valve is put forward to illustrate established models by numerical methods. The results indicate that the optimization models are effective to the reliability of engineering systems. It is our future work to consider an interdependent competing failure model where degradation processes and shocks can accelerate each other.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

TY  - JOUR
AU  - Qinqin Xu
AU  - Yuanguo Zhu
PY  - 2020
DA  - 2020/09/24
TI  - Uncertain Random Optimization Models Based on System Reliability
JO  - International Journal of Computational Intelligence Systems
SP  - 1498
EP  - 1506
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200915.002
DO  - 10.2991/ijcis.d.200915.002
ID  - Xu2020
ER  -