Abstract
Consider a coherent system, in which the degradation processes of its performance characteristics are positively correlated, this paper systematically investigates a bivariate degradation model of such a system. To analyze the accelerated degradation data, a flexible class of bivariate stochastic processes are proposed to incorporate the effects of environmental stress variables and the dependency between two degradation processes is modeled by a copula function. A two-step system reliability analysis approach is developed and it is implemented with the Hamiltonian Monte Carlo algorithm. Simulation studies validate this approach and the consequences of model misspecification are evaluated too. Furthermore, two real-world examples are presented to demonstrate the applicability of the proposed modeling framework of system reliability on correlated degradation processes.
Original language | English (US) |
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Article number | 106618 |
Journal | Reliability Engineering and System Safety |
Volume | 193 |
DOIs | |
State | Published - Jan 2020 |
Keywords
- Accelerated degradation test
- Bayesian inference
- Copula function
- Hamiltonian Monte Carlo
- Multivariate model
- System reliability
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Industrial and Manufacturing Engineering