Open Access
Volume 39, Number 2, April 2021
Page(s) 439 - 447
Published online 09 June 2021
  1. Ye Z S, Xie M. Stochastic modelling and analysis of degradation for highly reliable products[J]. Applied Stochastic Models in Business and Industry, 2015, 31(1):16–32 [Article] [Google Scholar]
  2. Zhao J B, Si S B, Cai Z Q. A multi-objective reliability optimization for reconfigurable systems considering components degradation[J]. Reliability Engineering & System Safety, 2019, 183: 104–115 [Article] [Google Scholar]
  3. Zhang F D, Ng H K T, Shi Y M. Mis-specification analysis of Wiener degradation models by using f-divergence with outliers[J]. Reliability Engineering & System Safety, 2019, 195: 106751 [Article] [Google Scholar]
  4. Zhang Z X, Si X S, Hu C H, et al. Degradation data analysis and remaining useful life estimation: a review on Wiener-process-based methods[J]. European Journal of Operational Research, 2018, 271(3):775–796 [Article] [Google Scholar]
  5. Hu Qiguo, Gao Zhan. A reliability evaluation method for system's dependent competition failure and multi-parameter degradation failure[J]. Journal of Northwestern Polytechnical University, 2019, 37(6):1191–1199 [Article] (in Chinese) [Google Scholar]
  6. Jiang R. A multivariate CBM model with a random and time-dependent failure threshold[J]. Reliability Engineering & System Safety, 2013, 119: 178–185 [Article] [Google Scholar]
  7. Yang Yuanjian. Research on reliability evaluation for mechanical products based on degradation modelling[D]. Chengdu: University of Electronic Science and Technology of China, 2016 (in Chinese) [Google Scholar]
  8. Cui L R, Chen J H, Li X C. Balanced reliability systems under Markov processes[J]. IISE Transactions, 2019, 51(9):1025–1035 [Article] [Google Scholar]
  9. Fu J C, Wu T L. Boundary crossing probabilities for high-dimensional Brownian motion[J]. Journal of Applied Probability, 2016, 53(2):543–553 [Article] [Google Scholar]
  10. Pan Z Q, Balakrishnan N, Sun Q, et al. Bivariate degradation analysis of products based on Wiener processes and copulas[J]. Journal of Statistical Computation and Simulation, 2013, 83(7):1316–1329 [Article] [Google Scholar]
  11. Yan Weian. Research on the method of storage reliability for torpedo[D]. Xi'an: Northwestern Polytechnical University, 2014 (in Chinese) [Google Scholar]
  12. Kong D J, Balakrishnan N, Cui L R. Two-phase degradation process model with abrupt jump at change point governed by Wiener process[J]. IEEE Trans on Reliability, 2017, 66(4):1345–1360 [Article] [Google Scholar]
  13. Wang X L, Jiang P, Guo B, et al. Real-time reliability evaluation for an individual product based on change-point gamma and Wiener process[J]. Quality and Reliability Engineering International, 2014, 30(4):513–525 [Article] [Google Scholar]
  14. Jiang R. Optimization of alarm threshold and sequential inspection scheme[J]. Reliability Engineering & System Safety, 2010, 95(3):208–215 [Article] [Google Scholar]
  15. Dong Q L, Cui L R, Si S B. Reliability and availability analysis of stochastic degradation systems based on bivariate Wiener processes[J]. Applied Mathematical Modelling, 2020, 79: 414–433 [Article] [Google Scholar]
  16. Wang W B. An overview of the recent advances in delay-time-based maintenance modelling[J]. Reliability Engineering & System Safety, 2012, 106: 165–178 [Article] [Google Scholar]
  17. Zhao X, Guo X X, Wang X Y. Reliability and maintenance policies for a two-stage shock model with self-healing mechanism[J]. Reliability Engineering & System Safety, 2018, 172: 185–194 [Article] [Google Scholar]
  18. Zhang S, Lyu R N, Si S B, et al. Reliability analysis of systems with common cause failure based on stress-strength interference model[J]. Journal of Shanghai Jiaotong University, 2018, 23(5):707–710 [Article] [Google Scholar]
  19. Zhu W J, Fouladirad M, BÉRenguer C. Multi-level maintenance policy based on a multi-component system with two independent failure modes[J]. Reliability Engineering & System Safety, 2016, 153: 50–63 [Article] [Google Scholar]
  20. Dong Q L, Cui L R. A study on stochastic degradation process models under different types of failure thresholds[J]. Reliability Engineering & System Safety, 2019, 181: 202–212 [Article] [Google Scholar]
  21. Qiu Q A, Cui L R. Reliability evaluation based on a dependent two-stage failure process with competing failures[J]. Applied Mathematical Modelling, 2018, 64: 699–712 [Article] [Google Scholar]
  22. Yang L, Ma X B, Zhao Y. A condition-based maintenance model for a three-state system subject to degradation and environmental shocks[J]. Computers & Industrial Engineering, 2017, 105: 210–222 [Article] [Google Scholar]
  23. Liu T Y, Pan Z Q, Sun Q, et al. Residual useful life estimation for products with two performance characteristics based on a bivariate Wiener process[J]. Journal of Risk and Reliability, 2017, 231(1):69 80 [Article] [Google Scholar]
  24. Zhang Y, Jia X, Guo B. Bayesian framework for satellite rechargeable lithium battery synthesizing bivariate degradation and lifetime data[J]. Journal of Central South University, 2018, 25(2):418–431 [Article] [Google Scholar]
  25. Xu A C, Shen L J, Wang B X, et al. On modeling bivariate Wiener degradation process[J]. IEEE Trans on Reliability, 2018, 67(3):897–906 [Article] [Google Scholar]
  26. Duan F J, Wang G J, Wang H. Inverse Gaussian process models for bivariate degradation analysis: a Bayesian perspective[J]. Communications in Statistics-Simulation and Computation, 2018, 47(1):166–186 [Article] [Google Scholar]
  27. Sacerdote L, Tamborrino M, Zucca C. First passage times of two-dimensional correlated processes: analytical results for the Wiener process and a numerical method for diffusion processes[J]. Journal of Computational and Applied Mathematics, 2016, 296: 275–292 [Article] [Google Scholar]

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