Preventive maintenance for coherent systems considering postponed replacement

IF 1.3 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Applied Stochastic Models in Business and Industry Pub Date : 2024-02-29 DOI:10.1002/asmb.2851

Majid Asadi

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Abstract

One primary objective of reliability engineering is to achieve optimal maintenance of technical systems, which ensures they remain in good operating condition. This paper proposes an age-based preventive optimal maintenance policy for $n$ -component coherent systems. Under this proposed strategy, the system begins operating at $t = 0$ and undergoes preventative maintenance (PM) at a time $T_{p}$ . If the system fails before $T_{p}$ , it will be replaced with a new one. If the system is still functioning at time $T_{p}$ , an assessment is made based on the number of failed components to determine whether the system should be replaced or allowed to continue operating. If the number of failures at $T_{p}$ is below a predetermined threshold $m$ , the PM time $T_{p}$ is postponed and a new PM time $T_{N}$ will be scheduled, and the system continues operating in the interval $(T_{p}, T_{N})$ . Otherwise, the entire system is preventively replaced at $T_{p}$ with a new one. In this scenario, we use a cost function to determine the optimal values of decision variables $T_{p}$ , $T_{N}$ , and $m$ . To examine the effectiveness of our proposed model, we analyze some examples of coherent systems using graphical and numerical methods.

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考虑推迟更换的连贯系统的预防性维护

可靠性工程的一个主要目标是实现技术系统的最佳维护，确保其保持良好的运行状态。本文针对 n$$ n$$ 组件连贯系统提出了一种基于年龄的预防性优化维护策略。根据该策略，系统在 t=0$$ t=0$ 开始运行，并在 Tp$$ {T}_p$ 时进行预防性维护（PM）。如果系统在 Tp$$ {T}_p $$ 之前出现故障，则会被新系统取代。如果系统在 Tp$$ {T}_p $$ 时仍在运行，则会根据故障部件的数量进行评估，以决定是更换系统还是允许系统继续运行。如果在 Tp$$ {T}_p $$ 时的故障数量低于预定阈值 m$$ m $$，则推迟 PM 时间 Tp$$ {T}_p $$，并安排新的 PM 时间 TN$$ {T}_N$ $$，系统在间隔 (Tp,TN)$$ \left({T}_p,{T}_N\right) $$ 内继续运行。否则，整个系统将在 Tp$$ {T}_p $$ 时预防性地更换为新系统。在这种情况下，我们使用成本函数来确定决策变量 Tp$$ {T}_p $$、TN$$$ {T}_N $$和 m$$ m $$的最优值。为了检验我们提出的模型的有效性，我们使用图形和数值方法分析了一些相干系统的实例。

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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.

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