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Component importance based on dependence measures

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Abstract

We discuss the construction of component importance measures for binary coherent reliability systems from known stochastic dependence measures by measuring the dependence between system and component failures. We treat both the time-dependent case in which the system and its components are described by binary random variables at a fixed instant as well as the continuous time case where the system and component life times are random variables. As dependence measures we discuss covariance and mutual information, the latter being based on Shannon entropy. We prove some basic properties of the resulting importance measures and obtain results on importance ordering of components.

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References

  • Ash R (1965) Information theory. Wiley, New York

    MATH  Google Scholar 

  • Barlow RE, Proschan F (1975a) Statistical theory of reliability and life testing. Holt, Rinehart and Winston, New York

    MATH  Google Scholar 

  • Barlow RE, Proschan F (1975b) Importance of system components and fault tree events. Stoch Proc Appl 3:153–173

    Article  MathSciNet  MATH  Google Scholar 

  • Beichelt F, Tittmann P (2012) Reliability and maintenance. Networks and systems. CRC Press, Boca Raton

    MATH  Google Scholar 

  • Birnbaum ZW (1969) On the importance of different components in a multicomponent system. In: Krishnaiah PR (ed) Multivariate analysis II. Academic Press, New York

  • Boland PJ, Proschan F (1983) The reliability of \(k\) out of \(n\) systems. Ann Probab 11:760–764

    Article  MathSciNet  MATH  Google Scholar 

  • Boland PJ, El-Neweihi E (1995) Measures of component importance in reliability theory. Comput Oper Res 22:455–463

    Article  MATH  Google Scholar 

  • Cheok MC, Parry GW, Sherry RR (1998) Use of importance measures in risk-informed regulatory applications. Reliab Eng Syst Saf 72:213–226

    Article  Google Scholar 

  • Ebrahimi N, Soofi ES, Soyer R (2010) Information measures in perspective. Int Stat Rev 78:383–412

    Article  MATH  Google Scholar 

  • Ebrahimi N, Jalali NY, Soofi ES, Soyer R (2014a) Importance of components for a system. Econom Rev 33:395–420

    Article  MathSciNet  Google Scholar 

  • Ebrahimi N, Jalali NY, Soofi ES (2014b) Comparison, utility, and partition of dependence under absolutely continuous and singular distributions. J Multivar Anal 254:427–442

    MathSciNet  MATH  Google Scholar 

  • Ebrahimi N, Soofi ES, Soyer R (2015) Information theory and Bayesian reliability : recent advances. In: Paganoni AM, Secchi P (eds) Advances in complex data modeling and computational methods in statistics (contributions to statistics). Springer, Cham, pp 87–102

    Google Scholar 

  • Esary JD, Proschan F, Walkup DW (1967) Association of random variables, with applications. Ann Math Stat 38:1466–1474

    Article  MathSciNet  MATH  Google Scholar 

  • Kimeldorf G, Sampson AR (1989) A framework for positive dependence. Ann Inst Statist Math 41:31–45

    MathSciNet  MATH  Google Scholar 

  • Kuo W, Zhu X (2012a) Some recent advances on importance measures in reliability. IEEE Trans Reliab 61:344–360

    Article  Google Scholar 

  • Kuo W, Zhu X (2012b) Relations and generalizations of importance measures in reliability. IEEE Trans Reliab 61:659–674

    Article  Google Scholar 

  • Kuo W, Zhu X (2012c) Importance measures in reliability, risk, and optimization. Wiley, Chichester

    Book  Google Scholar 

  • Lehmann EL (1966) Some concepts of dependence. Ann Math Statist 5:1137–1153

    Article  MathSciNet  MATH  Google Scholar 

  • Natvig B (1979) A suggestion of a new measure of importance of system components. Stoch Proc Appl 9:319–330

    Article  MathSciNet  MATH  Google Scholar 

  • Natvig B (1982) On the reduction of the remaining system lifetime due to the failure of a specific component. J Appl Probab 19:642–652 (Correction: J Appl Probab 20:713 (1983))

  • Natvig B (1985) New light on measures of importance of system components. J Scand Statist 12:43–54

    MathSciNet  MATH  Google Scholar 

  • Natvig B (2011) Measures of component importance in nonrepairable and repairable multistate strongly coherent systems. Methodol Comput Appl Probab 13:523–547

    Article  MathSciNet  MATH  Google Scholar 

  • Natvig B, Gåsemyr J (2009) New results on the Barlow–Proschan and Natvig measures of component importance in nonrepairable and repairable systems. Methodol Comput Appl Probab 11:603–620

    Article  MathSciNet  MATH  Google Scholar 

  • Norros I (1986) Notes on Natvig’s measure of importance of system components. J Appl Probab 23:736–747

    Article  MathSciNet  MATH  Google Scholar 

  • Rényi A (1959) On measures of dependence. Acta Math Acad Sci Hung 10:441–451

    Article  MathSciNet  MATH  Google Scholar 

  • Scarsini M (1984) On measures of concordance. Stochastica 8:201–218

    MathSciNet  MATH  Google Scholar 

  • Schweizer B, Wolf EF (1981) On nonparametric measures of dependence for random variables. Ann Statist 9:879–885

    Article  MathSciNet  MATH  Google Scholar 

  • Shaked M, Shanthikumar G (2007) Stochastic orders. Springer, New York

    Book  MATH  Google Scholar 

  • Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423

    Article  MathSciNet  MATH  Google Scholar 

  • van der Borst M, Schoonakker H (2001) An overview of PSA importance measures. Reliab Eng Syst Saf 72:241–245

    Article  Google Scholar 

Download references

Acknowledgements

Thanks are due to the referees whose comments led to a significant improvement of the paper.

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Correspondence to Mario Hellmich.

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Hellmich, M. Component importance based on dependence measures. Math Meth Oper Res 87, 229–250 (2018). https://doi.org/10.1007/s00186-017-0617-x

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  • DOI: https://doi.org/10.1007/s00186-017-0617-x

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