Estimating bearing lower bound reliability without past failures

Reuben Lim Chi Keong and David Mba

Journal of Risk and Reliability, 2013, vol. 227, issue 2, 199-206

Abstract: For operators and maintainers, extension of maintenance intervals is desired to alleviate costs. For aircraft and helicopter components, traditional failure time-based reliability assessment methods can seldom be applied as the reliability is often very high and failure data are often not available. In this article, different approaches using Nelson’s method, Weibull plot equation and probabilistic damage model to estimate a rolling element bearing’s reliability without failure data are reviewed. Two methods are then proposed to improve the reliability assessing the Weibull plot equation and the probabilistic damage model approaches by estimating their lower confidence bounds. In the first proposed method, Monte Carlo simulation is applied with the Weibull plot equation to obtain the variation in the Weilbull slope parameter and then estimate the lower confidence bound. In the second proposed method, probabilistic damage accumulation model is applied to assess the bearing reliability and bootstrap techniques are applied to obtain the lower confidence bound. Both methods are used to assess the reliability of extending the replacement interval of a helicopter gearbox bearing from 2000 to 3000 h and are shown to perform better with the use of Nelson’s method.

Keywords: Rolling element bearing; reliability without failure data; Weibull plot equation; Monte Carlo simulation; damage accumulation models (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1748006X12470419 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:227:y:2013:i:2:p:199-206

DOI: 10.1177/1748006X12470419

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().