In this work, the statistical methods for the reliability of repairable systems have been used to produce a methodology capable to estimate the annualized failure rate of a pipeline population from the historical failure data of multiple pipeline systems. The proposed methodology provides point and interval estimators of the parameters of the failure intensity function for two of the most commonly applied stochastic models: the homogeneous Poisson process and the power law process. It also provides statistical tests for assessing the adequacy of the stochastic model assumed for each system and testing whether all systems have the same model parameters. In this way, the failure data of multiple pipeline systems are only merged in order to produce a generic failure intensity function when all systems follow the same stochastic model. This allows statistical and tolerance uncertainties to be addressed adequately. The proposed methodology is outlined and illustrated using real-life failure data of oil and gas pipeline systems.

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