Bayesian inference with overlapping data: Methodology for reliability estimation of multi-state on-demand systems

Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability

Volumn 226, Issue 3, 2012, Pages 283-294

  Jacksonn, C ^a   Mosleh, A ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

Bayesian analysis; downwards inference; multi state systems; overlapping hierarchical data

Indexed keywords

BAYESIAN NETWORKS; COMPUTER CIRCUITS; HIERARCHICAL SYSTEMS; INFERENCE ENGINES; RELIABILITY THEORY;

BAYESIAN ANALYSIS; DOWNWARDS INFERENCES; LIKELIHOOD FUNCTIONS; MULTI-STATE SYSTEM; OVERLAPPING HIERARCHICAL DATUM; RELIABILITY BLOCK DIAGRAMS; RELIABILITY ESTIMATION; STRUCTURE FUNCTIONS;

RELIABILITY ANALYSIS;

EID: 84873884514     PISSN: 1748006X     EISSN: 17480078     Source Type: Journal    
DOI: 10.1177/1748006X11424104     Document Type: Article

References (17)

1. Hoyland A., Rausand M. System reliability theory: models, statistical methods, and applications. 2, (John Wiley & Sons, Inc.). 2004.
2. Kumamoto H., Henley E. J. Probabilistic risk assessment and management for engineers and scientists. 2, 2000 (Wiley-IEEE Press). Wiley-IEEE Press.
3. HickmanJ. W.PRA procedures guide: a guide to the performance of probabilistic risk assessments for nuclear power plants, NUREG/CR-2300, 1983, vol. 1.
4. Lisnianski A., Levitin G. Multi state system reliability: assessment, optimization, and applications. Word Scientific Publishing ; 2003 :
5. Li C.-Y., Chen X., Yi X.-S., Tao J.-Y.. Interval-valued reliability analysis of multi-state systems. IEEE Trans. Reliab.. 2011 ; 60 (1). 323-330
6. Jackson C., Mosleh A.. Downwards propagating inference: Bayesian analysis of complex on-demand systems. 56th Annual Reliability and Maintainability Symposium (RAMS) ; San Jose ;..
7. Jackson C., Mosleh A.. Bayesian inference with overlapping data: methodology for system reliability estimation of binary-state on-demand systems. Proc. IMechE, Part O: J. Risk and Reliability. :
8. Graves T., Hamada M.S., Koehler A., Martz H.F.. A fully Bayesian approach for combining multi-level information in multi-state fault tree quantification. Reliab. Eng. Syst. Saf.. 2007 ; 92: 1476-1483
9. Klamann R., Koehler A. Computational Social and Organizational Systems. Indiana: South Bend ; 2005 :
10. Mastran D., Singpurwalla N.. Incorporating component and system test data into the same assessment: a Bayesian approach. Op. Res.. 1976 ; 24 (3). 491-499
11. Martz H., Waller R., Fickas E.. Bayesian reliability analysis of series systems of binomial subsystems and components. Technometrics. 1988 ; 30 (2). 143-154
12. Martz H., Waller R.. Bayesian reliability analysis of complex series/parallel systems of binomial subsystems and components. Technometrics. 1990 ; 32: 407-416
13. Johnson V., Graves T., Hamada M.S., Reese C.S. Bayesian statistics. Bernardo J. M. Berger J. O. Dawid A. P. Heckerman D. Smith A. F. M. West M., ed. London: Oxford University Press ; 2003: 199-213.
14. Hamada M.S., Martz H.F., Reese C.S., Graves T., Johnson V., Wilson A.G.. A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation. Reliab. Eng. Sys. Saf.. 2004 ; 86: 297-305
15. Barlow R., Wu A.. Coherent systems with multi-state components. Math. Op. Res.. 1978 ; 3 (4). 275-281
16. Graves T., Klamann R.M., Koehler A.C., Martz H.F.. Using simultaneous higher-level and partial lower-level data in reliability assessments. Reliab. Eng. Sys. Saf.. 2008 ; 93 (8). 1273-1279
17. Shannon C. E.. A mathematical theory of communication. Bell Sys. Tech. J.. 1948 ; 27: 279-423