A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data

D.M. Louit, R. Pascual and A.K.S. Jardine

Reliability Engineering and System Safety, 2009, vol. 94, issue 10, 1618-1628

Abstract: Many times, reliability studies rely on false premises such as independent and identically distributed time between failures assumption (renewal process). This can lead to erroneous model selection for the time to failure of a particular component or system, which can in turn lead to wrong conclusions and decisions. A strong statistical focus, a lack of a systematic approach and sometimes inadequate theoretical background seem to have made it difficult for maintenance analysts to adopt the necessary stage of data testing before the selection of a suitable model. In this paper, a framework for model selection to represent the failure process for a component or system is presented, based on a review of available trend tests. The paper focuses only on single-time-variable models and is primarily directed to analysts responsible for reliability analyses in an industrial maintenance environment. The model selection framework is directed towards the discrimination between the use of statistical distributions to represent the time to failure (“renewal approach†); and the use of stochastic point processes (“repairable systems approach†), when there may be the presence of system ageing or reliability growth. An illustrative example based on failure data from a fleet of backhoes is included.

Keywords: Trend testing; Time to failure; Model selection; Repairable systems; NHPP (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:94:y:2009:i:10:p:1618-1628

DOI: 10.1016/j.ress.2009.04.001

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