Autopsy data analysis for a series system with active redundancy under a load-sharing model

Man Ho Alpha LING, Hon Keung Tony NG, Ping Shing CHAN, Narayanaswamy BALAKRISHNAN

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2 Citations (Scopus)

Abstract

The failure of any component within a series system results in the failure of the system. Incorporating active redundancy into a system generally improves its reliability and availability. This type of system does not belong to the category of coherent systems, and thus those results on coherent systems are not applicable. Hence, it is of great interest to develop statistical methodologies that perform well for inference on reliability of redundancy systems. In a life-test for multicomponent systems, component lifetimes may not be observable, but one may observe a set of components that failed along with the system. The data available in this form are called autopsy data, and, in this case, lifetime information on some of the components is missing. In this paper, we consider an equal load-sharing model and develop an expectation-maximization algorithm for estimating system reliability characteristics based on such an autopsy data. The load-sharing parameter indicates whether incorporating active redundancy improves system reliability or induces rapid failure of the system. The performance of the proposed methodology is then evaluated through Monte Carlo simulations and then illustrated with two numerical examples. Copyright © 2016 IEEE.
Original languageEnglish
Pages (from-to)957-968
JournalIEEE Transactions on Reliability
Volume65
Issue number2
Early online dateFeb 2016
DOIs
Publication statusPublished - Jun 2016

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Citation

Ling, M. H., Ng, H. K. T., Chan, P. S., & Balakrishnan, N. (2016). Autopsy data analysis for a series system with active redundancy under a load-sharing model. IEEE Transactions on Reliability, 65(2), 957-968.

Keywords

  • Active redundancy
  • Autopsy data
  • Cumulative exposure model
  • Exponential distribution
  • Load-sharing model
  • Series system