基于直角三角形模糊数的水轮机结构系统模糊可靠性

IF 1.8 Q3 ENGINEERING, INDUSTRIAL Journal of Quality in Maintenance Engineering Pub Date : 2021-09-28 DOI:10.1108/jqme-02-2021-0017
P. Dhiman, Amit Kumar
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引用次数: 1

摘要

目的研究埃及石油天然气公司涡轮机结构在模糊环境和工作标准下的可靠性、平均故障时间(MTTF)、平均修复时间(MTTR)和平均无故障时间(MTBF)性能。本文研究了各种部件的故障对整个油气系统涡轮机结构的影响。设计/方法/方法为了克服各种组件的可用数据的不确定性问题,提出了考虑右三角广义模糊数(RTrGFN)来表示数据中达到一定容差的不确定性。此外,利用Lambda-Tau方法和右广义三角模糊数(RTrGFN)的算术运算计算了可靠性指标;在模糊的环境下。预计故障率和维修时间将呈指数级增长。正在对结构部件进行排序,以决定维修的优先级。原创性/价值本文研究了系统在不同扩展/容忍度(如15%、25%和50%的清晰数据)下的性能。它有助于预测范围值中的实际结果。为了提高系统的性能,系统中最重要的项目需要更多的关注。为此,作者通过排名找到了敏感部分。对于排序,提出了一种扩展的方法,通过使用右三角广义模糊数来找到系统的敏感单元。本文探讨了系统中最敏感和最不敏感的组件,这有助于维护部门计划维护行动。
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Fuzzy reliability of a turbines structure system using the right triangular fuzzy number
PurposeThe purpose of this paper is to investigate the performance of a turbine structure of the oil and gas Egyptian company in terms of reliability, mean time to failure (MTTF), mean time to repair (MTTR) and mean time between failures (MTBF) under fuzzy environment and working criteria. This paper examines the impact of the failure of various components on the complete turbine structure of the oil and gas system.Design/methodology/approachTo overcome the problem of uncertain behavior of available data for various components, the right triangular generalized fuzzy number (RTrGFN) is proposed to be taken into the account to express the uncertainty which attains some tolerance in data. Furthermore, reliability indices are calculated with the help of the Lambda Tau method and the arithmetic operations on right generalized triangular fuzzy numbers (RTrGFN).FindingsThis paper explores the reliability of a repairable 3 out of 4 structure of turbines and along with the other parameters namely MTTF, MTTR and MTBF; under a fuzzy environment. Failure rates and repair times are expected to be exponential. The ranking of components of the structure is being found to decide the priority for maintenance.Originality/valueThis paper investigates the performance of the system with different spread/tolerance like 15%, 25% and 50% of crisp data. It helps to predict realistic results in the range value. To enhance the system's performance, the most important item of the system requires greater attention. For this, the authors find the sensitive part by ranking. For ranking, an extended approach has been developed to find the sensitive unit of the system by using the right triangular generalized fuzzy number. This paper explores the most and least sensitive component of the system, which helps the maintenance department to plan the maintenance action.
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来源期刊
Journal of Quality in Maintenance Engineering
Journal of Quality in Maintenance Engineering Engineering-Safety, Risk, Reliability and Quality
CiteScore
4.00
自引率
13.30%
发文量
24
期刊介绍: This exciting journal looks at maintenance engineering from a positive standpoint, and clarifies its recently elevatedstatus as a highly technical, scientific, and complex field. Typical areas examined include: ■Budget and control ■Equipment management ■Maintenance information systems ■Process capability and maintenance ■Process monitoring techniques ■Reliability-based maintenance ■Replacement and life cycle costs ■TQM and maintenance
期刊最新文献
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