Reliability function of a class of time-dependent systems with standby redundancy

By applying shortest path analysis in stochastic networks, we introduce a new approach to obtain the reliability function of time-dependent systems with standby redundancy. We assume that not all elements of the system are set to function from the beginning. Upon the failure of each element of the active path in the reliability graph, the system switches to the next path. Then, the corresponding elements are activated and consequently the connection between the input and the output is established. It is also assumed each element exhibits a constant hazard rate and its lifetime is a random variable with exponential distribution. To evaluate the system reliability, we construct a directed stochastic network called E-network, in which each path corresponds with a minimal cut of the reliability graph. We also prove that the system failure function is equal to the density function of the shortest path of E-network. The shortest path distribution of this new constructed network is determined analytically using continuous-time Markov processes.

[1]  Marc Bouissou,et al.  A new formalism that combines advantages of fault-trees and Markov models: Boolean logic driven Markov processes , 2003, Reliab. Eng. Syst. Saf..

[2]  Francesco Maffioli,et al.  Fishman's sampling plan for computing network reliability , 2001, IEEE Trans. Reliab..

[3]  James J. Solberg,et al.  The use of cutsets in Monte Carlo analysis of stochastic networks , 1979 .

[4]  David Coppit,et al.  Combining various solution techniques for dynamic fault tree analysis of computer systems , 1998, Proceedings Third IEEE International High-Assurance Systems Engineering Symposium (Cat. No.98EX231).

[5]  Richard E. Barlow,et al.  Statistical Theory of Reliability and Life Testing: Probability Models , 1976 .

[6]  A. Lešanovský Multistate Markov models for systems with dependent units , 1988 .

[7]  P. Humphreys,et al.  Dependent failures developments , 1991 .

[8]  Pitu B. Mirchandani,et al.  Shortest distance and reliability of probabilistic networks , 1976, Comput. Oper. Res..

[9]  J. R. English,et al.  A discretizing approach for stress/strength analysis , 1996, IEEE Trans. Reliab..

[10]  J. J. Martin Distribution of the Time Through a Directed, Acyclic Network , 1965 .

[11]  Kaung-Hwa Chen,et al.  A multivariant exponential shared-load model , 1993 .

[12]  Antoine Rauzy,et al.  Efficient algorithms to assess component and gate importance in fault tree analysis , 2001, Reliab. Eng. Syst. Saf..

[13]  Antoine Rauzy,et al.  New algorithms for fault trees analysis , 1993 .

[14]  George S. Fishman,et al.  A Monte Carlo Sampling Plan for Estimating Network Reliability , 1984, Oper. Res..

[15]  Terje Aven Reliability/Availability evaluations of coherent systems based on minimal cut sets , 1985 .

[16]  Kuolung Hu,et al.  A new approach to system reliability , 2001, IEEE Trans. Reliab..

[17]  J. J. Higgins,et al.  Stochastic modelling of human-performance reliability , 1988 .

[18]  George S. Fishman A Comparison of Four Monte Carlo Methods for Estimating the Probability of s-t Connectedness , 1986, IEEE Transactions on Reliability.

[19]  James L. Peterson,et al.  Petri net theory and the modeling of systems , 1981 .

[20]  K. Grace,et al.  Probabilistic Reliability: An Engineering Approach , 1968 .

[21]  V. G. Kulkarni,et al.  Shortest paths in networks with exponentially distributed arc lengths , 1986, Networks.

[22]  H. Frank,et al.  Shortest Paths in Probabilistic Graphs , 1969, Oper. Res..

[23]  J. C. Cluley,et al.  Probabilistic Reliability: an Engineering Approach , 1968 .

[24]  Derek Ray,et al.  A Primer of Reliability Theory , 1990 .