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The bathtub curve is a particular shape of a failure rate graph. This graph is used in reliability engineering and deterioration modeling. The 'bathtub' refers to the shape of a line that curves up at both ends, similar in shape to a bathtub. The bathtub curve has 3 regions: The first region has a decreasing failure rate due to early failures.
Failure rate is the frequency with which any system or component fails, expressed in failures per unit of time. It thus depends on the system conditions, time interval, and total number of systems under study. [1]
The failure types for integrated circuit (IC) components follow the classic bath tub curve. There is infant mortality, which is decreasing failure rate typically due to manufacturing defects. A low constant failure rate which is random in nature. Wear out failures are increasing failures due to aging semiconductor degradation mechanisms.
A well-known model to show the probability of failure of an asset throughout its life is called bathtub curve. This curve is made of three main stages: infant failure, constant failure, and wear out failure. In infrastructure asset management the dominant mode of deterioration is because of aging, traffic, and climatic attribute.
In semiconductor devices, problems in the device package may cause failures due to contamination, mechanical stress of the device, or open or short circuits. Failures most commonly occur near the beginning and near the ending of the lifetime of the parts, resulting in the bathtub curve graph of failure rates.
Replacing the weak components would prevent premature failure, infant mortality failure, or other latent defects. When the equivalent lifetime of the stress is extended into the increasing part of the bathtub-like failure-rate curve, the effect of the burn-in is a reduction of product lifetime. In a mature production it is not easy to determine ...
In other words, it is assumed that the system has survived initial setup stresses and has not yet approached its expected end of life, both of which often increase the failure rate. Assuming a constant failure rate implies that has an exponential distribution with parameter . Since the MTBF is the expected value of , it is given by the ...
In fact, the hazard rate is usually more informative about the underlying mechanism of failure than the other representations of a lifetime distribution. The hazard function must be non-negative, λ ( t ) ≥ 0 {\displaystyle \lambda (t)\geq 0} , and its integral over [ 0 , ∞ ] {\displaystyle [0,\infty ]} must be infinite, but is not ...