Discrete reliability-growth models based on a learning-curve property

A learning curve property, originally prescribed for describing reliability growth when time to failure is observed, is applied to discrete reliability growth processes for systems for which only discrete success or failure events are observed. Derivations leading to a well-known discrete reliability growth model are presented, and the role of implicit assumptions relating to testing strategy is identified. An alternative testing strategy, particularly appropriate for destructive testing of very expensive systems, is proposed and a new discrete reliability growth model is derived. Extensions to both types of discrete reliability growth models, which account for the distinction between assignable cause (readily correctable failure models) and nonassignable cause (state-of-the-art failure modes), are also provided. Parameter estimates for each of the models can be obtained via usual maximum likelihood procedures.<
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