Redundancy Allocation Problem in k-Out-Of-n Systems With Dependent and Heterogeneous Components

IF 1.5 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Applied Stochastic Models in Business and Industry Pub Date : 2025-03-03 DOI:10.1002/asmb.2932
Zohreh Zare, Somayeh Zarezadeh, Mahmood Kharrati-Kopaei
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Abstract

The aim of this paper is to investigate the problem of one and two active redundant components allocation in a k-out-of-n system with dependent components. Here, some necessary and sufficient conditions are presented under which the redundancies are optimally allocated to the system components based on the usual stochastic order criterion. In addition, it is shown that, unlike the independence mode, a redundant component is not necessarily allocated to the weakest component. Further, in the case of the two redundant components, the weak (strong) redundant component is not necessarily allocated to the stronger (weaker) component of the system. Some algorithms are also presented for calculating the reliability of the considered system under the assumption of dependency between the main and redundant components. Using different copula functions for describing the dependencies between components, various examples are given to illustrate the optimal allocation of redundant components.

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具有依赖和异构组件的k- of -n系统的冗余分配问题
本文的目的是研究具有相依分量的k / n系统中一个和两个主动冗余分量的分配问题。本文给出了基于通常的随机顺序准则的系统部件冗余度最优分配的充分必要条件。此外,与独立模式不同,冗余组件不一定分配给最弱的组件。此外,在两个冗余组件的情况下,弱(强)冗余组件不一定分配给系统的强(弱)冗余组件。在假定主部件和冗余部件相互依赖的情况下,给出了计算系统可靠性的一些算法。利用不同的联结函数来描述组件之间的依赖关系,给出了各种实例来说明冗余组件的最优分配。
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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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