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An Integrated Probabilistic Model for Assessing a Nanocomponent's Reliability

Part of: Stochastic processes Operations research and management science

Published online by Cambridge University Press:  14 July 2016

Nader Ebrahimi  and
Yarong Yang
Nader Ebrahimi*
Affiliation:
Northern Illinois University
Yarong Yang*
Affiliation:
University of California, Berkeley
*
∗ Postal address: Division of Statistics, Northern Illinois University, DeKalb, IL 60115, USA. Email address: [email protected]
∗∗ Postal address: Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720, USA.
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Abstract

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We construct an integrated probabilistic model to capture interactions between atoms of a nanocomponent. We then use this model to assess reliabilities of nanocomponents with different structures. Several properties of our proposed model are also described under a sparseness condition. The model is an extension of our previous model based on Markovian random field theory. The proposed integrated model is flexible in that pairwise relationship information among atoms as well as features of individual atoms can be easily incorporated. An important feature that distinguishes the integrated probabilistic model from our previous model is that the integrated approach uses all available sources of information with different weights for different types of interaction. In this paper we consider the nanocomponent at a fixed moment of time, say the present moment, and we assume that the present state of the nanocomponent depends only on the present states of its atoms.

Keywords

Associated random variableconditionally increasing in sequenceGibbs distributionGibbs samplingMarkov random fieldreliability

MSC classification

Secondary: 60G55: Point processes 90B25: Reliability, availability, maintenance, inspection
Type
Research Papers
Information
Journal of Applied Probability , Volume 48 , Issue 3 , September 2011 , pp. 832 - 842
Copyright
Copyright © Applied Probability Trust 2011 

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