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On Bayesian Estimation of System Reliability

Publication Type : Journal Article

Publisher : Microelectronics Reliability

Source : Microelectronics Reliability, Volume 33, Number 10, p.1455 - 1459 (1993)

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Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Computer Science, Electronics and Communication

Year : 1993

Abstract : For a system with n s-independent components, the uncertainty regarding the reliability of components for a fixed point of time is expressed by a Bayesian probability distribution. Using the moments of these distributions, the exact moments of the system reliability distribution are derived, from which a discrete probability density function is obtained on the basis of the principle of maximum entropy. Taking this distribution as a prior distribution for system reliability, a posterior density function for the system reliability is constructed either using the data obtained from life tests conducted at a system level or from field data. For tracking the evolution of the reliability distribution over time, a modified Kalman filter technique, along with use of a Bayesian procedure, is proposed. This method is simple, elegant and easy to compute.

Cite this Research Publication : Dr. Soman K. P. and Misra, K. B., “On Bayesian Estimation of System Reliability”, Microelectronics Reliability, vol. 33, pp. 1455 - 1459, 1993.

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