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An Optimal Condition Based Maintenance Strategy Using Inverse-Gaussian Degradation Process

机译:基于逆高斯劣化过程的基于最佳状态的维护策略

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Condition based maintenance (CBM) is a practical and effective way to guarantee the product availability. Recent years the optimization strategy of CBM is widely studied by researchers. For product with measurable degradation performance, degradation modeling plays an important role in CBM. Inverse Gaussian process has many superb properties in dealing with covariates and random effect. In this paper, a new CBM optimization model is developed basing on the nonlinear inverse Gaussian degradation model. With the constraint of cost, the optimal CBM strategy is obtained by maximizing availability of product. Specifically, we consider imperfect preventive maintenance and proposed a way to describe its influence. Finally, the proposed model is demonstrated by a numerical example.
机译:基于条件的维护(CBM)是一种确保产品可用性的实用有效方法。近年来CBM的优化策略被研究人员普遍研究。对于具有可测量的降解性能的产品,降解建模在CBM中起着重要作用。逆高斯进程在处理协变量和随机效果方面具有许多精湛的性质。本文介绍了一种新的CBM优化模型,基于非线性逆高斯降解模型。通过成本的约束,通过最大化产品的可用性来获得最佳CBM策略。具体而言,我们考虑不完美的预防性维护,并提出了一种描述其影响的方法。最后,通过数值示例对所提出的模型进行说明。

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