A review on degradation models in reliability analysis

Date

2010

Authors

Gorjian, N.
Ma, L.
Mittinty, M.
Yarlagadda, P.
Sun, Y.

Editors

Kiritsis, D.
Emmanouilidis, C.
Koronios, A.
J, J.

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Book chapter

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Event/exhibition information: Proceedings of the 4th World Congress on Engineering Asset Management, Athens, Greece, 28/09/2009-30/09/2009 Source details - Title: Engineering Asset Lifecycle Management, 2010 / Kiritsis, D., Emmanouilidis, C., Koronios, A., J, J. (ed./s), pp.369-384

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Abstract

With increasingly complex engineering assets and tight economic requirements, asset reliability becomes more crucial in Engineering Asset Management (EAM). Improving the reliability of systems has always been a major aim of EAM. Reliability assessment using degradation data has become a significant approach to evaluate the reliability and safety of critical systems. Degradation data often provide more information than failure time data for assessing reliability and predicting the remnant life of systems. In general, degradation is the reduction in performance, reliability, and life span of assets. Many failure mechanisms can be traced to an underlying degradation process. Degradation phenomenon is a kind of stochastic process; therefore, it could be modelled in several approaches. Degradation modelling techniques have generated a great amount of research in reliability field. While degradation models play a significant role in reliability analysis, there are few review papers on that. This paper presents a review of the existing literature on commonly used degradation models in reliability analysis. The current research and developments in degradation models are reviewed and summarised in this paper. This study synthesises these models and classifies them in certain groups. Additionally, it attempts to identify the merits, limitations, and applications of each model. It provides potential applications of these degradation models in asset health and reliability prediction

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Dissertation Note

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Link to a related website: http://eprints.qut.edu.au/27913/1/c27913.pdf, Open Access via Unpaywall

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Copyright 2010 Springer

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