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For highly reliable products, traditional accelerated life-test
(ALT)methods may not be practical to estimate the lifetimessince
the products are not likely to fail in a reasonable amount of
time.Hence, degradation tests are widely used to assess
thereliability of highly reliable products.However, for very-
highly reliable products, the degradation rate is too slowto
make useful inferences within a reasonable amount of time. In
this case,higher stresses are usually used to accelerate the
degradation rate anda suitable life-stress model is adopted to
extrapolate and estimate theproduct''s reliability at a design
stress. This method is called theaccelerated degradation test
(ADT).In designing an ADT, there are many important decision
variablessuch as the sample size, the length of a life-
testingand the inspection frequency at each stress level. These
variablesare influential tothe cost and the precision of data
analysis.Therefore, this thesis focuses on designing an ADT to
enhance the precisionof data analysis. An intuitive on-line
procedure isproposed to determine an appropriate termination
time for ADTs.Furthermore, by using the criterion of minimizing
the variance of estimatingthe $(100p)th$ percentile of the
product''s lifetime distributionand the product''s mean-time-to-
failure (MTTF),a nonlinear integer programming is established to
determine the optimal(a)the sample size to test, (b) the length
of a life-testing, and (c)the inspection frequency at each
stress level.
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