Bayesian Inference for Reliability of Systems and Networks Using the Survival Signature.

The concept of survival signature has recently been introduced as an alternative to the signature for reliability quantification of systems. While these two concepts are closely related for systems consisting of a single type of component, the survival signature is also suitable for systems with multiple types of component, which is not the case for the signature. This also enables the use of the survival signature for reliability of networks. In this article, we present the use of the survival signature for reliability quantification of systems and networks from a Bayesian perspective. We assume that data are available on tested components that are exchangeable with those in the actual system or network of interest. These data consist of failure times and possibly right-censoring times. We present both a nonparametric and parametric approach.

[1]  Ludi Simpson,et al.  'Estimating with confidence' and hindsight: New UK small-area population estimates for 1991 , 2008 .

[2]  Frank P. A. Coolen,et al.  Nonparametric predictive inference for failure times of systems with exchangeable components , 2012 .

[3]  Richard E. Brown,et al.  Electric Power Distribution Reliability , 2002 .

[4]  Serkan Eryilmaz Review of recent advances in reliability of consecutive k-out-of-n and related systems , 2010 .

[5]  Francisco J. Samaniego,et al.  System Signatures and Their Applications in Engineering Reliability , 2007 .

[6]  James M. Flegal,et al.  Chapter 1 Implementing Markov chain Monte Carlo : Estimating with confidence , 2010 .

[7]  Frank P. A. Coolen,et al.  Nonparametric predictive inference for combined competing risks data , 2014, Reliab. Eng. Syst. Saf..

[8]  Frank P. A. Coolen,et al.  Nonparametric predictive inference for system failure time based on bounds for the signature , 2013 .

[9]  Louis J. M. Aslett,et al.  MCMC for inference on phase-type and masked system lifetime models , 2012 .

[10]  Francisco J. Samaniego,et al.  Linking Dominations and Signatures in Network Reliability , 2002 .

[11]  Narayanaswamy Balakrishnan,et al.  Exact nonparametric inference for component lifetime distribution based on lifetime data from systems with known signatures , 2011 .

[12]  Richard E. Barlow,et al.  Statistical Theory of Reliability and Life Testing: Probability Models , 1976 .

[13]  Francisco J. Samaniego,et al.  LINKING DOMINATIONS AND SIGNATURES IN NETWORK RELIABILITY THEORY , 2003 .

[14]  L. Tierney Markov Chains for Exploring Posterior Distributions , 1994 .

[15]  Richard Brown,et al.  Electric Power Distribution Reliability, Second Edition , 2008 .

[16]  Narayanaswamy Balakrishnan,et al.  Parametric inference for component distributions from lifetimes of systems with dependent components , 2012 .

[17]  F. Coolen,et al.  Generalizing the signature to systems with multiple types of components , 2013, SOCO 2013.

[18]  Andrew Gelman,et al.  Handbook of Markov Chain Monte Carlo , 2011 .

[19]  Frank P. A. Coolen,et al.  Citation for Published Item: Use Policy Nonparametric Predictive Inference for System Reliability Using the Survival Signature , 2022 .