渐增凸序相干系统寿命的比较

IF 1.5 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Francesco Buono, Franco Pellerey
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引用次数: 0

摘要

在可靠性文献中,随机阶数被广泛用于比较相干系统的性能,并为此提供了各种准则。特别地,我们找到了一个系统寿命随机大于具有相同寿命分布但结构函数不同的相同组件的另一个系统的充分条件。这类已知的结果与一些最相关的随机阶有关,但在文献中没有为众所周知的递增凸阶(icx)提供条件。在这里,我们描述了当其他更强阶的条件不适用时,相干系统的两个寿命在这种随机意义上具有可比性的条件。并给出了实例说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Comparisons of Coherent Systems' Lifetimes in the Increasing Convex Order

Comparisons of Coherent Systems' Lifetimes in the Increasing Convex Order

Stochastic orders have been widely used in reliability literature to compare the performances of coherent systems, and various criteria have been provided on this purpose. In particular, sufficient conditions have been found for the lifetime of a system to be stochastically larger than that of another system having the same components with identically distributed lifetimes but a different structure function. Known results of this kind concern some of the most relevant stochastic orders, but in the literature no conditions have been provided for the well-known increasing convex order (icx). Here we describe conditions such that two lifetimes of coherent systems are comparable in this stochastic sense when conditions for other stronger orders do not apply. Illustrative examples are also given.

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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
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.
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