DISCRETE RELIABILITY-GROWTH MODELS BASED ON A LEARNING-CURVE PROPERTY

A learning-curve property, originally prescribed for describing reliab ility growth when time to failure is observed, is applied to discrete reliability-growth processes for systems for which only discrete succe ss or failure events are observed (eg, a missile or torpedo). Derivati ons leading to a well-known discrete reliability-growth model are pres ented, and the role of implicit assumptions relating to testing strate gy is identified. An alternative testing strategy, particularly approp riate for destructive test 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 di stinction between assignable cause (readily correctable failure modes) and non-assignable cause (state-of-the-art failure modes), are also p rovided. Parameter estimates for each of the models can be obtained vi a usual maximum likelihood procedures. Each of the derived discrete re liability-growth models is legitimate in the sense that ft accommodate s monotonic growth in reliability as testing progresses through consec utive system configurations. The use of any particular discrete reliab ility-growth model cannot be supported by the learning-curve property, however, unless the appropriate assumptions identified in this paper are satisfied.