Estimation System Storage Reliability By Accelerated Parameter Drifting

To meet increasing competition, get products to market in the shortest possible time, and satisfy heightened customer expectations, products must be made more robust and fewer failures must be observed in a short development period. In this circumstance, assessing product reliability based on degradation data at high stress levels becomes necessary. This assessment is accomplished through accelerated degradation tests (ADT). These tests involve over stress testing in which instead of life product performance is measured as it degrades over time.With the development of engineering and science technology, many modern products have longer lifetimes and greater reliability than those in the past. Thus, lifetime measurements and degradation measurements take much more time than they used to. It is therefore difficult to observe failure times, or even degradation measurements, under normal storage conditions.In this research, starting from the practical backgrounds and problems of engineering, based on the system storage reliability model with storage initial failure, R(t) = P(T≥t|T>0)P(T>0) = R₀R_s(t),t≥0 , we establish anacademic system storage reliability model incorporating the degradation date and the failure date extrapolated by accelerated failure laws from accelerated degradation test(ADT) which quicken the process of parameter drifting to estimate the system storage reliability.The primary objective for this research is to develop the inference procedures for extrapolation the storage reliability of system in normal conditions based on ADT data without the need of observing actual failures. Although physical failures are not needed in ADT, one usually defines failure as the first time when the degradation process exceeds a pre-specified threshold, so that the degradation path can be correlated to product reliability. In order to model such degradation over time and make inference about thefailure, we assume a the Arrhenius law Gaussian process model with driftv_L=ζe^θ/L for degradation combined with failure data in an accelerateddegradation testing.