초록

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Abstract ▼ AI-Helper

Reliability prediction provides a rational basis for design decisions such as the choice between alternative concepts, choice of part quality levels, derating factors to be applied, use of proven versus state-of-the-art techniques, and other factors. For this reasons, reliability prediction is essen...

Reliability prediction provides a rational basis for design decisions such as the choice between alternative concepts, choice of part quality levels, derating factors to be applied, use of proven versus state-of-the-art techniques, and other factors. For this reasons, reliability prediction is essential functions in developing space systems. The worth of the quantitative expression lies in the information conveyed with the numerical value and the use which is made of that information and reliability prediction should be initiated early in the configuration definition stage to aid in the evaluation of the design and to provide a basis for item reliability allocation (apportionment) and establishing corrective action priorities. Reliability models and predictions are updated when there is a significant change in the item design availability of design details, environmental requirements, stress data, failure rate data, or service use profile. In this paper, the procedure, selection of reliability data and methods for space system reliability prediction is presented.

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