备用切换故障下冗余再加工系统的可靠性分析

IF 2.3 2区 工程技术 Q3 ENGINEERING, INDUSTRIAL Quality Technology and Quantitative Management Pub Date : 2023-01-01 DOI:10.1080/16843703.2022.2132450
Kuo-Hsiung Wang, Chia-Huang Wu, T. Yen
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引用次数: 1

摘要

随着互联网和硬件的飞速发展,云计算在各行各业得到了广泛的应用。使用高质量和可靠的通信设备以及有效的维修系统的支持服务是必不可少的。本文提出了一种用于多虚拟机在线数据分析服务的云计算系统的潜在应用。假设主虚拟机和备用虚拟机都不可靠。本研究分析了一种具有热备和开关故障的重审机维修系统。当维修设施不可访问时,故障机器加入重试池,并在随机周期后尝试访问维修服务。采用拉普拉斯变换技术和矩阵解析方法推导了系统可靠性和平均无故障时间的性能度量。最后给出了系统参数对系统性能影响的数值结果。
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Reliability analysis of redundant retrial machining system subject to standby switching failure
ABSTRACT With the rapid development of the Internet and hardware, cloud computing has been widely applied in various industries. Supporting services using high-quality and reliable communications equipment with an effective repair system is essential. A potential application of a cloud computing system for online data analysis services with multiple virtual machines is presented herein. The primary and standby virtual machines are both assumed to be unreliable. In this study, we analyze a retrial machine repair system with warm standbys and switching failure. When the repair facility is inaccessible, the failed machine joins a retrial pool and tries to access the repair service after a random period. The Laplace transform technique and matrix-analytical method are employed to derive the system performance measures of the reliability and mean time to failure. Moreover, numerical results are provided to investigate the effects of system parameters on system performances.
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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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