退化部件失效所隐含的随机依赖模型

IF 1.3 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Applied Stochastic Models in Business and Industry Pub Date : 2023-11-15 DOI:10.1002/asmb.2831

Emilio Casanova Biscarri, Sophie Mercier, Carmen Sangüesa

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引用次数: 0

摘要

这里考虑了一个n个$$ n $$组件的系统，其中组件劣化由非递减的时间尺度lsamvy过程建模。当一个组件失效时，会引起幸存组件的时间尺度函数的突然变化，从而使组件随机依赖。在这种新的依赖模型下，计算了相干系统的可靠度函数。其次，我们研究了有序失效时间的分布，并建立了一些正相关性质。我们还提供了具有不同参数的两种依赖模型失效时间在通常的多变量随机顺序下的随机比较结果。最后，通过数值实验验证了理论结果。

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A model for stochastic dependence implied by failures among deteriorating components

A system of $n$ components is here considered, with component deterioration modeled by non decreasing time-scaled Lévy processes. When a component fails, a sudden change in the time-scaling functions of the surviving components is induced, which makes the components stochastically dependent. We compute the reliability function of coherent systems under this new dependence model. We next study the distribution of the ordered failure times, and establish some positive dependence properties. We also provide stochastic comparison results in the usual multivariate stochastic order between failure times of two dependence models with different parameters. Finally, some numerical experiments illustrate the theoretical results.

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来源期刊

Applied Stochastic Models in Business and Industry 数学-数学跨学科应用

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.