Hierarchical Modelling of Industrial System Reliability with Probabilistic Logic

Kamil Dedecius, Pavel Ettler

Abstract

The use of Bayesian methods in dynamic assessment of system reliability is inevitably limited by computational difficulties arising from non-conjugate prior distributions. This contribution proposes an alternative framework, based on the combination of Bayesian methods and the subjective logic. The advantage of the former – consistent and exhaustive representation of available statistical knowledge, is extended by the latter, allowing computationally feasible combination of this knowledge at any level of the observed system using logic operations. The resulting methodology is currently under development in order to enlarge the capability of an intended novel industrial hierarchical condition monitoring system.

References

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Paper Citation


in Harvard Style

Dedecius K. and Ettler P. (2014). Hierarchical Modelling of Industrial System Reliability with Probabilistic Logic . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 133-139. DOI: 10.5220/0005007001330139


in Bibtex Style

@conference{icinco14,
author={Kamil Dedecius and Pavel Ettler},
title={Hierarchical Modelling of Industrial System Reliability with Probabilistic Logic},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={133-139},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005007001330139},
isbn={978-989-758-039-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Hierarchical Modelling of Industrial System Reliability with Probabilistic Logic
SN - 978-989-758-039-0
AU - Dedecius K.
AU - Ettler P.
PY - 2014
SP - 133
EP - 139
DO - 10.5220/0005007001330139