Review Articles

Dynamic stress–strength reliability estimation of system with survival signature

Yiming Liu ,

Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an, Shaanxi, People's Republic of China

scott_ymliu@163.com

Yimin Shi ,

Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an, Shaanxi, People's Republic of China

Xuchao Bai ,

Department of Applied Mathematics, Northwestern Polytechnical University, Xi'an, Shaanxi, People's Republic of China

Bin Liu

Department of Applied Mathematics, Taiyuan University of Science and Technology, Taiyuan, Shanxi, People's Republic of China

Pages 181-195 | Received 14 Mar. 2018, Accepted 28 Sep. 2018, Published online: 08 Oct. 2018,
  • Abstract
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ABSTRACT

In this paper, we proposed a dynamic stress–strength model for coherent system. It is supposed that the system consists of n components with initial random strength and each component is subjected to random stresses. The stresses, applied repeatedly at random cycle times, will cause the degradation of strength. In addition, the number of cycles in an interval is assumed to follow a Poisson distribution. In the case of the strength and stress random variables following exponential distributions, the expression for the reliability of the proposed dynamic stress–strength model is derived based on survival signature. The reliability is estimated by using the best linear unbiased estimation (BLUE). Considering the Type-II censored failure times, the best linear unbiased predictors (BLUP) for the unobserved coherent system failure times are developed based on the observed failure times. Monte Carlo simulations are performed to compare the BLUE of parameters with different values and compute the BLUP. A real data set is also analysed for an illustration of the findings.

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