Maintenance planning estimations and policies optimization for single-unit systems using Hawkes processes

IF 2.3 2区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Lirong Cui, Fengming Kang, Jingyuan Shen
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引用次数: 0

Abstract

ABSTRACT Maintenance planning and optimizations are very important issues in both theory and practice. In this paper, Hawkes processes, a tool for description of self-excited failure effects, are used to model the failure processes of single-unit systems under the assumption of neglected repair times. For such degraded single-unit systems, some maintenance planning estimations such as the distribution, mean and variance of failures or repairs by time , reliability, mean cost of maintenance, mean and variance of system lifetime are presented under the maximal entropy assumption on repair effects. Meanwhile, two optimization problems are developed by considering the lifetime mean of the single-unit system and total maintenance cost as objective functions and constraints alternatively. We have proved that both optimization problems can reduce to two simplified optimal cases, respectively, and their optimal policies are increasing stepwise sequences of increasing rates of failure rates, which greatly reduce the scope of optimal solutions. The relationships between the estimations and the optimizations are discussed. Furthermore, the detailed optimal maintenance policies for a special case are given as well including an algorithm.
使用霍克斯流程对单机系统进行维护计划评估和策略优化
维修计划和优化是理论和实践中非常重要的问题。本文利用描述自激失效效应的工具Hawkes过程,在忽略维修时间的假设下,对单单元系统的失效过程进行建模。针对这类退化单单元系统,在最大熵假设下,给出了故障或维修的时间分布、可靠性、平均维修成本、系统寿命均值和方差等维修计划估计。同时,将单机系统寿命均值和总维护费用作为目标函数和约束条件交替考虑,提出了两个优化问题。我们证明了这两个优化问题都可以分别简化为两个最优情况,并且它们的最优策略都是故障率递增的逐步递增序列,这大大减小了最优解的范围。讨论了估计和优化之间的关系。在此基础上,给出了一种特殊情况下的最优维护策略,并给出了算法。
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
Quality Technology and Quantitative Management
Quality Technology and Quantitative Management ENGINEERING, INDUSTRIAL-OPERATIONS RESEARCH & MANAGEMENT SCIENCE
CiteScore
5.10
自引率
21.40%
发文量
47
审稿时长
>12 weeks
期刊介绍: Quality Technology and Quantitative Management is an international refereed journal publishing original work in quality, reliability, queuing service systems, applied statistics (including methodology, data analysis, simulation), and their applications in business and industrial management. The journal publishes both theoretical and applied research articles using statistical methods or presenting new results, which solve or have the potential to solve real-world management problems.
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