Abstract
The purpose of this chapter is to describe basic concepts of applying statistical methods to MSSs reliability assessment. Here we will stay in the Markov model framework and consider modern methods for estimation of transition intensity rates. But first basic concepts of statistical estimation theory will be briefly presented. Readers who need more fundamental and detailed development of estimation theory may wish to consult such texts as Bickel and Doksum (2007) or Lehmann and Casella (2003). Engineering applications can be found in Hines and Montgomery (1997), Ayyub and McCuen (2003), etc.
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References
Ayyub B, McCuen R (2003) Probability, statistics and reliability for engineers and scientists. Chapman & Hall/CRC, London, NY
Bickel P, Doksum K (2007) Mathematical statistics. Pearson Prentice Hall, New Jersey
Billinton R, Allan R (1996) Reliability evaluation of power system, Plenum, New York
Epstein B (1960) Estimation from life test data. Technometrics 2:447–454
Fisher R (1925) Theory of statistical estimation. Proceedings of the Cambridge Philosophical Society, 22:700-725
Fisher R (1934) Two new properties of mathematical likelihood. Proceedings of Royal Society, A, 144: 285–307
Gertsbakh I (2000) Reliability theory with application to preventive maintenance. Springer, London
Hines W, Montgomery D (1997) Probability and statistics in engineering and management science. Wiley, New York
International Standard IEC60605-4 (2001) Procedures for determining point estimates and confidence limits for equipment reliability determination tests. International Electrotechnical Commission, Geneva, Switzerland
Korolyuk V, Swishchuk A (1995) Semi-Markov random evolutions. Kluwer, Dordrecht
Lawless J (2002) Statistical models and methods for lifetime data. Wiley, New York
Lehmann E, Casella G (2003) Theory of point estimation. Springer-Verlag, NY
Limnious N, Oprisan G (2000) Semi-Markov processes and reliability. Birhauser, Boston
Lisnianski A (2008) Point estimation of the transition intensities for a Markov multi-state system via output performance observation. In: Bedford T et al (eds) Advances in Mathematical Modeling for Reliability. IOS, Amsterdam
Lisnianski A, Jeager A (2000) Time-redundant system reliability under randomly constrained time resources. Reliab Eng Syst Saf 70:157–166
Lisnianski A, Levitin G (2003) Multi-state system reliability: assessment, optimization and applications. World Scientific Singapore
Meeker W, Escobar L (1998) Statistical methods for reliability data. Wiley, New York
Modarres M, Kaminskiy M, Krivtsov V (1999) Reliability engineering and risk analysis: a practical guide. Dekker, New York
Neyman J (1935) On the problem of confidence intervals. Ann Math Stat 6:111–116
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(2010). Statistical Analysis of Reliability Data for Multi-state Systems. In: Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers. Springer, London. https://doi.org/10.1007/978-1-84996-320-6_3
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DOI: https://doi.org/10.1007/978-1-84996-320-6_3
Publisher Name: Springer, London
Print ISBN: 978-1-84996-319-0
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