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http://dx.doi.org/10.5351/CKSS.2011.18.2.201

A Note on the Efficiency Based Reliability Measures for Heterogeneous Populations  

Cha, Ji-Hwan (Department of Statistics, Ewha Womans University)
Publication Information
Communications for Statistical Applications and Methods / v.18, no.2, 2011 , pp. 201-211 More about this Journal
Abstract
In many cases, populations in the real world are composed of different subpopulations. Furthermore, in addition to the heterogeneity in the lifetimes of items, there also could be the heterogeneity in the efficiency or performance of items. In this case, the reliability measures should be defined in a different way. In this article, we consider the mixture of stochastically ordered subpopulations. Efficiency based reliability measures are defined when the performance of items in the subpopulations has different levels. Discrete and continuous mixing models are studied. The concept of the association between the lifetime and the performance of items in subpopulations is defined. It is shown that the consideration of efficiency can change the shape of the mixture failure rate dramatically especially when the lifetime and the performance of items in subpopulations are negatively associated. Furthermore, the modelling method proposed in this paper is applied to the case when the stress levels of the operating environment of items are different.
Keywords
Heterogeneous population; failure rate; efficiency; transformed time scale; association;
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  • Reference
1 Block, H.W., Savits, T. H. andWondmagegnehu, E. T. (2003). Mixtures of distributions with increasing linear failure rates, Journal of Applied Probability, 40, 485–504.
2 Finkelstein, M. S. (2008). Failure Rate Modelling for Reliability and Risk, Springer, London.
3 Jensen, F. and Petersen, N. E. (1982). Burn-in, John Wiley, New York.
4 Gupta, R. C. and Warren, R. (2001). Determination of change points of nonmonotonic failure rates, Communications in Statistics-Theory and Methods, 30, 1903–1920.   DOI   ScienceOn
5 Jiang, R. and Murthy, D. N. P. (1995). Modelling failure rate by mixture of two Weibull distributions. IEEE Transactions on Reliability, 44, 477-488.   DOI   ScienceOn
6 Meeker,W. Q. and Escobar, L. A. (1993). A review of recent research and current issues of accelerated testing, International Statistical Review, 61, 147–168.
7 Navarro, J. and Hernandez, P. J. (2004). How to obtain bathtub-shaped failure rate models from normal mixtures, Probability in the Engineering and Informational Sciences, 18, 511–531.
8 Nelson, W. (1990). Accelerated Testing: Statistical Models, Test Plans, and Data Analysis, John Wiley & Sons Inc, New York.