具有依赖增量的随机退化描述的项目的年龄替代策略

IF 1.9 3区 工程技术 Q3 MANAGEMENT
Ji Hwan Cha;Maxim Finkelstein;Gregory Levitin
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引用次数: 3

摘要

我们考虑一种混合预防性维护策略。与经典的年龄替换模型一样,系统在失效或达到预定的年龄T时被替换。此外,在[0,T]中的某个中间时间,系统可以在达到预定的恶化水平时被替换。我们使用具有依赖增量的转换伽马过程来模拟退化。当该过程达到预定的确定性水平时,就会发生项目故障。结果表明,该策略优于经典策略,即实现了较低的长期成本率值。给出了详细的数值说明,并对模型的主要参数进行了灵敏度分析。本文的工作对维护建模做出了重要贡献,因为依赖增量可以更好地表示真实系统的退化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Age-replacement policy for items described by stochastic degradation with dependent increments
We consider a hybrid preventive maintenance policy. As in the classic model of age-replacement, a system is replaced either on failure or on reaching a predetermined age T. Additionally, it can be replaced on reaching a predetermined level of deterioration at some intermediate time in [0,T). We use a transformed gamma process with dependent increments to model the deterioration. A failure of an item occurs when this process reaches a predetermined deterministic level. We show that the proposed policy outperforms the classical one, that is, it achieves a lower value of the long-run cost rate. A detailed numerical illustration is presented and sensitivity analysis for the main parameters of the model is performed. The work in the paper makes an important contribution to maintenance modelling because dependent increments can better represent deterioration of a real system.
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来源期刊
IMA Journal of Management Mathematics
IMA Journal of Management Mathematics OPERATIONS RESEARCH & MANAGEMENT SCIENCE-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.70
自引率
17.60%
发文量
15
审稿时长
>12 weeks
期刊介绍: The mission of this quarterly journal is to publish mathematical research of the highest quality, impact and relevance that can be directly utilised or have demonstrable potential to be employed by managers in profit, not-for-profit, third party and governmental/public organisations to improve their practices. Thus the research must be quantitative and of the highest quality if it is to be published in the journal. Furthermore, the outcome of the research must be ultimately useful for managers. The journal also publishes novel meta-analyses of the literature, reviews of the "state-of-the art" in a manner that provides new insight, and genuine applications of mathematics to real-world problems in the form of case studies. The journal welcomes papers dealing with topics in Operational Research and Management Science, Operations Management, Decision Sciences, Transportation Science, Marketing Science, Analytics, and Financial and Risk Modelling.
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