Abstract

System reliability and performance are improved by continuous improvement effort. The study of the increase in reliability as a function of time is the subject of reliability growth. Although the most well-known reliability growth model, the Duane model, is proposed more than thirty years ago, reliability growth analysis has attracted an increasing interest only recently because of the lack of time for testing and the high reliability of improved products leading to very few failures. In this paper we study a practical approach in reliability growth analysis. Based on the graphical plotting of failure data for some selected models, reliability can easily be estimated and predicted. This approach which is the original idea of the Duane model, overcomes the problem of parameter estimation and model validation that is usually complicated. It is especially useful when the model validation has to be done in order to select a suitable model. The approach, called the First-Model-Validation-Then-Parameter-Estimation approach, is simple and practical for the analysis of reliability growth data. We further develop some models and discuss their applicability in reliability engineering.

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