Stochastic comparisons of coherent systems with active redundancy at the component or system levels and component lifetimes following the accelerated life model

IF 1.3 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Applied Stochastic Models in Business and Industry Pub Date : 2023-09-12 DOI:10.1002/asmb.2822

Arindam Panja, Pradip Kundu, Biswabrata Pradhan

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引用次数: 0

Abstract

An effective way to increase system reliability is to use redundancies (spares) into the systems either in component level or in system level. In this prospect, it is a significant issue that which set of available spares providing better system reliability in some stochastic sense. In this paper, we derive sufficient conditions under which a coherent system with a set of active redundancy at the component level or the system level provide better system reliability than that of the system with another set of redundancy, with respect some stochastic orders. We have derived the results for the component lifetimes following accelerated life (AL) model. The results obtained help us to design more reliable systems by allocating appropriate redundant components from the set of available options for the same. Various examples satisfying the sufficient conditions of the theoretical results are provided. Some results are illustrated with real-world data.

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采用加速寿命模型，对在组件或系统层面具有主动冗余的连贯系统和组件寿命进行随机比较

提高系统可靠性的有效方法是在组件或系统中使用冗余（备件）。在这种前景下，一个重要的问题是，哪一组可用备件能在某种随机意义上提供更好的系统可靠性。在本文中，我们推导出了充分条件，在这些条件下，一个在组件级或系统级具有一组主动冗余的连贯系统，在某些随机阶次方面，比具有另一组冗余的系统提供更好的系统可靠性。我们按照加速寿命（AL）模型得出了组件寿命的结果。所获得的结果有助于我们从一系列可供选择的冗余组件中分配适当的冗余组件，从而设计出更可靠的系统。本文提供了满足理论结果充分条件的各种实例。一些结果用实际数据进行了说明。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.