The use of ARIMA models for reliability forecasting and analysis

Abstract

This paper investigates the approach to repairable system reliability forecasting based on the Autoregressive Integrated Moving Average (ARIMA) models. This time series technique makes very few assumptions and is very flexible. It is theoretically and statistically sound in its foundation and no a priori postulation of models is required when analysing failure data. An illustrative example on a mechanical system failures is presented. Comparison is also made with the traditional Duane model. It is concluded that ARIMA model is a viable alternative that gives satisfactory results in terms of its predictive performance. © 1998 Elsevier Science Ltd. All rights reserved.