关于多尝试最小修复和相应的计数过程

IF 1.3 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Applied Stochastic Models in Business and Industry Pub Date : 2023-09-13 DOI:10.1002/asmb.2819

Ji Hwan Cha, Maxim Finkelstein

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引用次数: 0

摘要

考虑最小修复项目。在实践中，最小修复可能不成功，在这种情况下，应重复修复。文章使用泊松过程的广义化 Polya-Aeppli 过程进行相应建模。文章推导出了一些对优化维护有用的特性。文章描述了不成功尝试概率随时间变化的情况下的重要概括。还讨论了如何将推导结果应用于获得具有多次尝试最小维修的系统的最佳更换时间。本研究通过详细的数值示例进行了说明。

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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On the multiattempt minimal repair and the corresponding counting process

Minimally repaired items are considered. In practice, minimal repair can be unsuccessful, and in this case, it should be repeated. The Polya-Aeppli process, which is a generalization of the Poisson process is used in the article for the corresponding modeling. Some properties, useful for optimal maintenance, are derived. An important generalization to the case when the probability of the unsuccessful attempt is time-dependent is described. An application of the derived results to obtaining the optimal time of replacement for a system with multiattempt minimal repairs is discussed. The study is illustrated by detailed numerical examples.

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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.