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General Conditions for Comparing the Reliability Functions of Systems of Components Sharing a Common Environment

Published online by Cambridge University Press:  14 July 2016

Steven T. Garren*
Affiliation:
University of Virginia
Donald St. P. Richards*
Affiliation:
University of Virginia
*
Postal address: 104 Halsey Hall, Division of Statistics, University of Virginia, Charlottesville, VA 22903, USA.
∗∗Postal address: 107 Halsey Hall, Division of Statistics, University of Virginia, Charlottesville, VA 22903, USA.

Abstract

We present general criteria for analyzing the crossing characteristics of RI, the reliability function of an m-of-n system of components operating within a laboratory (or test-bench) environment, and RO, the reliability function of the same system now operating subject to an external environment. Inside the laboratory the components' lifetimes may be dependently distributed, and the external environment is modeled using the general approach of Lindley and Singpurwalla (1986). Our techniques, which utilize results basic to the theory of order statistics, apply to broad classes of external environment models.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1998 

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References

Abramowitz, M., and Stegun, I.A. (1972). Handbook of Mathematical Functions. Dover, New York.Google Scholar
Bandyopadhyay, D., and Basu, A.P. (1990). On a generalization of a model by Lindley and Singpurwalla. Adv. Appl. Prob. 22, 498500.CrossRefGoogle Scholar
Barlow, R.E., and Proschan, F. (1981). Statistical Theory of Reliability and Life Testing. To Begin With, Silver Spring, MD.Google Scholar
Currit, A., and Singpurwalla, N.D. (1988). On the reliability of a system of components sharing a common environment. J. Appl. Prob. 26, 763771.Google Scholar
David, H.A. (1970). Order Statistics. Wiley, New York.Google Scholar
Gupta, P.L., and Gupta, R.D. (1990). A bivariate random environmental stress model. Adv. Appl. Prob. 22, 501503.Google Scholar
Hougaard, P. (1986). A class of multivariate failure time distributions. Biometrika 73, 671678.Google Scholar
Lindley, D.V., and Singpurwalla, N.D. (1986). Multivariate distributions for the life lengths of components of a system sharing a common environment. J. Appl. Prob. 23, 418431.CrossRefGoogle Scholar
Marshall, A.W., and Olkin, I. (1967). A multivariate exponential distribution. J. Amer. Statist. Assoc. 62, 3044.Google Scholar
Peköz, E., and Ross, S.M. (1995). A simple derivation of exact reliability formulas for linear and circular consecutive-k-of-n : F systems. J. Appl. Prob. 32, 554557.Google Scholar
Singpurwalla, N.D., and Youngren, M.A. (1993). Multivariate distributions induced by dynamic environments. Scand. J. Statist. 20, 251261.Google Scholar
Woodham, S.-A. and Richards, D.St.P. (1997). Comparison of system reliability functions under laboratory and common operating environments. J. Appl. Prob. 34, 536545.CrossRefGoogle Scholar
Youngren, M.A. (1991). Dependence in target element detection induced by the environment. Naval Res. Logist. 38, 567577.Google Scholar