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Pseudo-modular decompositions and ‘refined bounds’ for the interval reliability and the availability for binary coherent systems

Published online by Cambridge University Press:  01 July 2016

N. Mazars*
Affiliation:
University of Oslo

Abstract

‘Divide and conquer’ is a traditional approach in various fields of applied mathematics. In reliability, only modules have been proposed to decompose complex coherent systems. However, a system may include no modules, except ‘trivial’ ones. This paper is the second step of a study concerned with module generalizations : in the first step, pseudo-modules have been retained as the most general coherent subsystems which can yield a complete extension of the fundamental results concerning modules; in addition, it has been proved that they concern any binary coherent system; in this paper, it is shown that pseudo-modular decompositions are the most general coherent decompositions which can yield a complete extension of all the ‘refined bounds’ for the interval reliability and the availability currently proposed in terms of modular decompositions.

This study also yields some fundamental results to extend all the ‘refined bounds’ currently proposed for multistate coherent systems, using an easier approach.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 1989 

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References

1. Barlow, R. E. and Iyer, S. (1985) Computational complexity of coherent systems and the reliability polynomial. ORC85-6, Operations Research Center, University of California, Berkeley.Google Scholar
2. Barlow, R. E. and Proschan, F. (1965) Mathematical Theory of Reliability. Wiley, New York.Google Scholar
3. Barlow, R. E. and Proschan, F. (1975) Statistical Theory of Reliability and Life Testing; Probability Models. Holt Rinehart and Winston, New York. Reprinted (1981) by To Begin With, Silver Springs, MD.Google Scholar
4. Birnbaum, Z. W. and Esary, J. D. (1965) Modules of coherent binary systems. SIAM J. Appl. Math. 13, 444462.Google Scholar
5. Block, H. W. and Savits, T. H. (1982) A decomposition for multistate monotone systems. J. Appl. Prob. 19, 391402.Google Scholar
6. Bodin, L. D. (1970) Approximations to system reliability using a modular decomposition. Technometrics 12, 335344.Google Scholar
7. Butler, D. A. (1982) Bounding the reliability of multistate systems. Operat. Res. 30, 530544.CrossRefGoogle Scholar
8. Butterworth, R. W. (1972) A set theoretic treatment of coherent systems. SIAM J. Appl. Math. 22, 590598.Google Scholar
9. Chatterjee, P. (1975) Modularization of fault trees: a method to reduce the cost of reliability Analysis. In Reliability and Fault Tree Analysis, ed. Barlow, R. E., Fussel, J. B. and Singpurwalla, N. D., SIAM Conference Volume, Philadelphia, 101126.Google Scholar
10. Esary, J. D. and Marshall, A. W. (1964) System structure and the existence of a system life. Technometrics 6, 459462.Google Scholar
11. Esary, J. D. and Marshall, A. W. (1970) Coherent life functions. SIAM J. Appl. Math. 18, 810814.Google Scholar
12. Esary, J. D. and Proschan, F. (1963) Coherent structures of non-identical components. Technometrics 5, 191209.CrossRefGoogle Scholar
13. Esary, J. D. and Proschan, F. (1970) A reliability bound for systems of maintained interdependent components. J. Amer. Statist. Assoc. 65, 329338.Google Scholar
14. Esary, J. D., Proschan, F. and Walkup, D. W. (1967) Association of random variables with applications. Ann. Math. Statist. 38, 14661474.Google Scholar
15. Funnemark, E. and Natvig, B. (1985) Bounds for the availabilities in a fixed time interval for multistate monotone systems. Adv. Appl. Prob. 17, 638665.CrossRefGoogle Scholar
16. Hjort, N. L., Natvig, B. and Funnemark, E. (1985) The association in time of a Markov process with application to multistate reliability theory. J. Appl. Prob. 22, 473479.Google Scholar
17. Mazars, N. (1986a) Multinary systems and reliability models, from coherence to some kind of non-coherence. EUR Report 10629 EN, European Communities Commission, Joint Research Center, Ispra Establishment, Italy.Google Scholar
18. Mazars, N. (1986b) Some efficient deterministic weapons against complexity in reliability theory: coherent subsystems and pseudo-modules for coherent systems–Part I: the binary case. Statistical Research Report N. 4, University of Oslo.Google Scholar
19. Mazars, N. (1989a) Some efficient deterministic weapons against complexity in reliability theory: coherent subsystems and pseudo-modules for coherent systems–Part II: From the monotone binary case to the multinary case. (A series on a unified theory for coherent systems to tackle complexity in reliability; Research Report 3, in preparation.) Google Scholar
20. Mazars, N. (1989b) New lights on modules through their generalizations: coherent subsystems and pseudo-modules for binary coherent systems. Submitted for publication.Google Scholar
21. Natvig, B. (1980) Improved bounds for the availability and unavailability in a fixed time interval for systems of maintained interdependent components. Adv. Appl. Prob. 12, 200221.Google Scholar
22. Natvig, B. (1986) On upper bounds for the availabilities in a fixed time interval for multistate monotone systems. Adv. Appl. Prob. 18, 577578.Google Scholar
23. Rosenthal, A. (1975) A computer scientist looks at reliability computations. In Reliability and Fault Tree Analysis, ed. Barlow, R. E., Fussel, J. B. and Singpurwalla, N. D., SIAM Conference Volume, Philadelphia, 133152.Google Scholar
24. Ruschendorf, L. (1981) Weak association of random variables. J. Multivariate Anal. 11, 458461.Google Scholar