A practical procedure for the selection of time to failure models based on the assessment of trends in maintenance data. http://dx.doi.org/10.1016/j.ress.2009.04.001

Abstract

Many times, reliability studies rely on false premises such as the independent andidentically 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 lackof 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 election 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 industrialmaintenance 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.