When is Acceleration Unnecessary in a Degradation Test
When is Acceleration Unnecessary in a Degradation Test
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DOI：
10.5705/ss.202015.0357
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发表时间：
2018
影响因子：
1.4
通讯作者：
Z. Ye;Lanqing Hong
中科院分区：
文献类型：
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作者：
Z. Ye;Lanqing Hong
加速度广泛用于可靠性测试，以在短时间内产生足够的可靠性信息。从统计的角度来看，加速的成本是需要额外的参数来将加速变量与故障过程联系起来。当统计信息的增加不足以补偿额外参数的引入时，加速效率低下。这种情况在寿命测试中可能很少见，因为加速会产生更多故障，而故障比审查提供更多信息。然而，在退化测试中，高应力水平下的退化测量中包含的信息可能不会比正常使用条件下的信息高很多；在这方面，加速可能并不总是必要的。本研究确定了使用一些常见随机过程模型（包括维纳过程、伽玛过程和逆高斯 (IG) 过程）时不需要加速的情况。我们假设降解速率和降解过程的波动性都是加速变量的函数。引入加速度关系指数来统一文献中看到的不同类型的加速度关系。结果表明，当加速关系指数至少为1时，加速总是低效的。否则，加速的必要性取决于模型参数的值以及加速关系指数。这些结果使用一类称为指数色散 (ED) 类的随机过程模型进行统一。给出了一个数值例子来说明该过程。
Acceleration is widely used in reliability tests to yield sufficient reliability information within a short time frame. From the statistical point of view, the cost of acceleration is that additional parameters are needed to link the accelerating variables to the failure process. When the increase of statistical information is insufficient to compensate the introduction of additional parameters, acceleration is inefficient. This scenario may be rare in a life test, as acceleration yields more failures and failure is more informative than censoring. In a degradation test, however, information contained in a degradation measurement under high stress levels may not be much higher than that under normal use conditions; in this connection, acceleration may not be always necessary. This study identifies situations where acceleration is unnecessary when some common stochastic process models are used, including the Wiener, gamma, and inverse Gaussian (IG) processes. We assume that both the degradation rate and the volatility of degradation process are functions of the accelerating variable. An acceleration relation index is introduced to unify different kinds of acceleration relations seen in the literature. It is shown that when the acceleration relation index is at least one, acceleration is always inefficient. Otherwise, the necessity of acceleration depends on values of the model parameters as well as the acceleration relation index. These results are unified using a class of stochastic process models called the exponential dispersion (ED) class. A numerical example is given to illustrate the procedure.