Abstract

An overview of the development and implementation of a computerized reliability prediction model is presented. The model utilizes historical system life data to analyze the life distribution of various types of components. The resulting component life distribution estimates are then used to predict the reliability of new system configurations. This approach is based on the theory of competing risks, but is unique in that it allows for the analysis of a pooled set of life data, i.e., life data from different types of systems, to obtain component estimates. The advantage of the approach lies in the fact that it yields component reliabilities based upon their performance in actual operating systems. The model and various issues critical to its successful implementation are presented. An example to illustrate the model's use is presented. >

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