A Load Sharing System Reliability Model With Managed Component Degradation

A Load Sharing System Reliability Model With Managed Component Degradation
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DOI:
10.1109/tr.2014.2315965
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发表时间:
2014-09-01
影响因子:
5.9
通讯作者:
Walls, Lesley
Walls, Lesley
中科院分区:
计算机科学2区
文献类型:
--
作者:
Ye, Zhisheng;Revie, Matthew;Walls, Lesley

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受影响的自来水公司的工业问题的启发,我们开发了一个模型的负载共享系统,操作员调度工作负载的组件的方式,管理其退化。我们假设退化是主要的故障类型,并且系统不会由于冲击而突然失效。通过推导系统的退化失效时间,产生系统失效概率的估计,并且可以获得最优设计,以最小化未来系统的长期平均成本。该模型可用于支持资产维护和设计决策。我们的模型是在一组共同的核心假设下开发的。也就是说,操作员分配工作以平衡所有组件的劣化条件的水平,以实现系统性能。假设系统在累积工作负载达到某个随机阈值时被替换。我们采用累积工作负载作为总使用量的度量,因为它代表了组件退化的主要原因。我们将系统的累积工作量建模为单调递增的平稳随机过程。假设一个部件退化失效的累积工作负荷服从逆高斯分布。通过一个工业问题的实例,说明了该模型在不同操作场景下的应用。
Motivated by an industrial problem affecting a water utility, we develop a model for a load sharing system where an operator dispatches work load to components in a manner that manages their degradation. We assume degradation is the dominant failure type, and that the system will not be subject to sudden failure due to a shock. By deriving the time to degradation failure of the system, estimates of system probability of failure are generated, and optimal designs can be obtained to minimize the long run average cost of a future system. The model can be used to support asset maintenance and design decisions. Our model is developed under a common set of core assumptions. That is, the operator allocates work to balance the level of the degradation condition of all components to achieve system performance. A system is assumed to be replaced when the cumulative work load reaches some random threshold. We adopt cumulative work load as the measure of total usage because it represents the primary cause of component degradation. We model the cumulative work load of the system as a monotone increasing and stationary stochastic process. The cumulative work load to degradation failure of a component is assumed to be inverse Gaussian distributed. An example, informed by an industry problem, is presented to illustrate the application of the model under different operating scenarios.