Optimal maintenance policy for imperfect production systems using reliability function and defect rate

IF 1.3 4区数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Applied Stochastic Models in Business and Industry Pub Date : 2024-01-04 DOI:10.1002/asmb.2843

Jyh-Wen Ho, Yeu-Shiang Huang, Peng-Tsi Huang

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引用次数: 0

Abstract

This study examines how a manufacturer can improve the robustness of an imperfect production system by implementing maintenance activities, which can be measured in terms of system reliability and product failure rate. A two-dimensional maintenance policy comprising system reliability and the product defect rate is proposed to assess maintenance activity costs. The optimal thresholds of the two dimensions are analyzed to investigate the trade-off between cost and system quality. A numerical example is provided to verify the proposed model's effectiveness. The results showed that the less stable the system, the greater the total costs incurred; therefore, lower stringent thresholds may be set to prevent frequent maintenance. Moreover, a sensitivity analysis is performed to investigate the essential parameters that significantly affect maintenance decisions. The results showed that the thresholds of the reliability function and defect rate significantly impact total costs. Any inaccurate assessment of system usage could lead to incorrect estimations and a substantial increase in cost.

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利用可靠性函数和缺陷率优化不完善生产系统的维护政策

本研究探讨了制造商如何通过实施维护活动来提高不完善生产系统的稳健性，维护活动可以用系统可靠性和产品故障率来衡量。本文提出了一种由系统可靠性和产品故障率组成的二维维护策略，用于评估维护活动成本。分析了两个维度的最佳阈值，以研究成本与系统质量之间的权衡。提供了一个数值示例来验证所提模型的有效性。结果表明，系统越不稳定，产生的总成本就越高；因此，可以设置较低的严格阈值来防止频繁维护。此外，还进行了敏感性分析，以研究对维护决策有重大影响的基本参数。结果表明，可靠性函数和缺陷率的阈值对总成本有重大影响。对系统使用情况的任何不准确评估都可能导致估算错误和成本大幅增加。

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.