Abstract
The statistical nature of failures in repairable systems does not have a behaviour similar to non-repairable systems. The statistical models developed for the study of the reliability of repairable systems mostly based on the application of stochastic processes. However, there is a group of prediction models for reliability based on time series analysis. Below are the results and conclusions of the application of simple regression models in the escalators Avante model (TNE), in order to assess their potential use by maintenance organizations.
Highlights
Much of the developed statistical models for the study of the reliability of repairable systems based on the application of stochastic processes in which a failure of an element is a random variable, and once repaired the failure is another random variable, which may or may not have equal probability density function
The Non-Homogeneous Poisson Processes (NHPP) model applies if the repairable system Time Between Failure (TBF) data shown to be independent and non-stationary, being the Power Law Process (PLP) the most extended (Crow, 1975)
Reliability models based on time series analysis are an alternative to models based on stochastic processes, when limited consumption of human and technical resources is required in the processing of data and tests, as well as obtaining results quickly
Summary
Much of the developed statistical models for the study of the reliability of repairable systems based on the application of stochastic processes in which a failure of an element is a random variable, and once repaired the failure is another random variable, which may or may not have equal probability density function. 27 simple regression models are tested and evaluated on the failure data of 40 escalators to model their reliability.
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