采用粒子群算法对具有随机维修和故障率的预热交换器系统进行可用性优化

Q2 Engineering
Ajay Kumar
{"title":"采用粒子群算法对具有随机维修和故障率的预热交换器系统进行可用性优化","authors":"Ajay Kumar","doi":"10.1504/IJRS.2018.10017230","DOIUrl":null,"url":null,"abstract":"The main objective of this study is to carry out performance analysis and availability maximisation with randomly selected failure and repair rates (FRR) of a Pre-Heat Exchanger (PHE) system of a brewery plant using the particle swarm algorithm. The behavioural analysis of each system is carried out by Markovian method and the schematic diagram of the PHE system represents various components and their connectivity (series/parallel/hybrid) whereas the transition diagram explores various possibilities and combinations of working states of the components i.e. full capacity working (FCW), reduced capacity working (RCW) and failed state (FS). The mathematical equations are formulated using the transition diagrams in order to carry out steady state availability (SSA) and transient state availability (TSA) analysis. The prediction of failure and repair rate to attain maximum availability of a system is done by using Particle Swarm Optimisation (PSO) technique. These results are beneficial for plant personnel by steering of failure and repair rates to achieve maximum availability.","PeriodicalId":39031,"journal":{"name":"International Journal of Reliability and Safety","volume":"12 1","pages":"327-347"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Availability optimisation of pre-heat exchanger system with random repair and failure rates using PSO\",\"authors\":\"Ajay Kumar\",\"doi\":\"10.1504/IJRS.2018.10017230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main objective of this study is to carry out performance analysis and availability maximisation with randomly selected failure and repair rates (FRR) of a Pre-Heat Exchanger (PHE) system of a brewery plant using the particle swarm algorithm. The behavioural analysis of each system is carried out by Markovian method and the schematic diagram of the PHE system represents various components and their connectivity (series/parallel/hybrid) whereas the transition diagram explores various possibilities and combinations of working states of the components i.e. full capacity working (FCW), reduced capacity working (RCW) and failed state (FS). The mathematical equations are formulated using the transition diagrams in order to carry out steady state availability (SSA) and transient state availability (TSA) analysis. The prediction of failure and repair rate to attain maximum availability of a system is done by using Particle Swarm Optimisation (PSO) technique. These results are beneficial for plant personnel by steering of failure and repair rates to achieve maximum availability.\",\"PeriodicalId\":39031,\"journal\":{\"name\":\"International Journal of Reliability and Safety\",\"volume\":\"12 1\",\"pages\":\"327-347\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Reliability and Safety\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJRS.2018.10017230\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Reliability and Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJRS.2018.10017230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 1

摘要

本研究的主要目的是使用粒子群算法对啤酒厂预热交换器(PHE)系统的随机选择故障和维修率(FRR)进行性能分析和可用性最大化。每个系统的行为分析是通过马尔可夫方法进行的,PHE系统的示意图代表了各种组件及其连接(串联/并联/混合),而过渡图探索了组件工作状态的各种可能性和组合,即满负荷工作(FCW),降低容量工作(RCW)和故障状态(FS)。为了进行稳态可用性(SSA)和瞬态可用性(TSA)分析,利用过渡图建立了数学方程。利用粒子群优化(PSO)技术对系统的故障和修复率进行预测,以达到系统的最大可用性。通过控制故障和维修率以实现最大可用性,这些结果对工厂人员是有益的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Availability optimisation of pre-heat exchanger system with random repair and failure rates using PSO
The main objective of this study is to carry out performance analysis and availability maximisation with randomly selected failure and repair rates (FRR) of a Pre-Heat Exchanger (PHE) system of a brewery plant using the particle swarm algorithm. The behavioural analysis of each system is carried out by Markovian method and the schematic diagram of the PHE system represents various components and their connectivity (series/parallel/hybrid) whereas the transition diagram explores various possibilities and combinations of working states of the components i.e. full capacity working (FCW), reduced capacity working (RCW) and failed state (FS). The mathematical equations are formulated using the transition diagrams in order to carry out steady state availability (SSA) and transient state availability (TSA) analysis. The prediction of failure and repair rate to attain maximum availability of a system is done by using Particle Swarm Optimisation (PSO) technique. These results are beneficial for plant personnel by steering of failure and repair rates to achieve maximum availability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
International Journal of Reliability and Safety
International Journal of Reliability and Safety Engineering-Safety, Risk, Reliability and Quality
CiteScore
1.00
自引率
0.00%
发文量
1
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信