Abstract
In this paper it is shown that the bathtub-curve (BTC) based time-derivative of the failure rate at the initial moment of time can be considered as a suitable criterion of whether burn-in testing (BIT) should or does not have to be conducted. It is also shown that the above criterion is, in effect, the variance of the random statistical failure rate (SFR) of the mass-produced components that the product manufacturer received from numerous vendors, whose commitments to reliability were unknown, and their random SFR might vary therefore in a very wide range, from zero to infinity. A formula for the non-random SFR of a product comprised of mass-produced components with random SFRs was derived, and a solution for the case of the normally distributed random SFR was obtained.
Highlights
Burn-in testing (BIT) [1,2,3,4,5,6,7,8,9,10] has for many years been an accepted practice for detecting and eliminating early failures in newly fabricated electronic products prior to shipping the “healthy” ones that survived BIT to customers
Application of the probabilistic design for reliability (PDfR)/FOAT/Boltzmann-Arrhenius-Zhurkov’s equation (BAZ) concept will be able, hopefully, answer this question for the given manufacturing technology, but, most importantly, will be able to establish the appropriate elevated stresses and their levels, and decide on the effective BIT duration to minimize the number of devices that will be destroyed and the time of testing
Λ(t) is time-dependent failure rate, λ0 is its steady-state minimum, λ1 is its initial value at the beginning of the infant therefore mortality portionplanned (IMP), t1 is the duration of this portion, λ2 is the final value of the failure rate at the end of the wear-out portion, t2 is the duration of this portion, and the exponents n1 and n2 are expressed through the fullnesses β 1 and β 2 of the BTC infant-mortality and the wear-out β portions as n1,2 = 1−1,2 β 1,2
Summary
Burn-in testing (BIT) [1,2,3,4,5,6,7,8,9,10] has for many years been an accepted practice for detecting and eliminating early failures in newly fabricated electronic products prior to shipping the “healthy” ones that survived BIT to customers. Depending on the anticipated operation conditions of the product and testing capabilities of a particular manufacturer, BIT can be based on temperature cycling, elevated temperatures, voltage, current, humidity, random vibrations, and so on, or, since the principle of superposition does not work in the reliability engineering—on the appropriate combination of these stressors. The thermal stress, caused by the change in temperature, is combined in these tests with dynamic (shocks, random vibrations) loading. Such a temperature-dynamic bias is thought to provide worst-case operating conditions [11,12]. High BIT stresses products, might thereby their lifetime It is unclear, to what extent it happens not reducing only eliminate “freaks”, but could cause permanent damage to the main population of :. BIT vehicle, is unable to provide any information on that
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