A structured framework for performance optimization using JBLTO, FCOPRAS and FCODAS methodologies

IF 1.8 Q3 ENGINEERING, INDUSTRIAL
Nand Gopal, Dilbagh Panchal
{"title":"A structured framework for performance optimization using JBLTO, FCOPRAS and FCODAS methodologies","authors":"Nand Gopal, Dilbagh Panchal","doi":"10.1108/jqme-11-2021-0087","DOIUrl":null,"url":null,"abstract":"PurposeThe proposed hybridized framework provides a new performance optimization-based paradigm for analysing the failure behaviour of paneer unit (PU) in the dairy industry.Design/methodology/approachA novel fuzzy Jaya-based Lambda–Tau Optimization (JBLTO) approach-based mathematical modelling was developed for calculating various reliability indices of the considered unit. Failure mode and effect analysis (FMEA) was carried using qualitative information gathered from system's expert opinions. Fuzzy-complex proportional assessment (FCOPRAS) approach was integrated within FMEA to recognize the most critical failure causes associated with various subsystem/components.FindingsThe availability of the unit falls by 0.053% as the uncertainty level increases from ±15 to ±25% and further decreases to 0.323% as the uncertainty level increases from ±25 to ±60%. Failure causes, namely wearing in gears of gearbox (MST4), an impeller's cavitation and/or corrosion (CFP4), winding failure of electric motor (WS9), were recognized as the most critical failure causes with FCOPRAS final performance scores of 100, 100 and 100 and fuzzy combinative distance-based assessment (FCODAS) resultant assessment score of 0.5997, 1.1898 and 1.6135.Originality/valueJBLTO approach-based reliability results were compared with traditional particle swarm optimization-based Lambda–Tau (PSOBLT) and traditional fuzzy Lambda–Tau (FLT) approaches for confirming the downward trend in the system's availability. The ranking results of qualitative analysis are compared with the implementation of FCODAS technique. Sensitivity analysis was executed to evaluate the robustness of the proposed hybridized framework.","PeriodicalId":16938,"journal":{"name":"Journal of Quality in Maintenance Engineering","volume":" ","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quality in Maintenance Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jqme-11-2021-0087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 2

Abstract

PurposeThe proposed hybridized framework provides a new performance optimization-based paradigm for analysing the failure behaviour of paneer unit (PU) in the dairy industry.Design/methodology/approachA novel fuzzy Jaya-based Lambda–Tau Optimization (JBLTO) approach-based mathematical modelling was developed for calculating various reliability indices of the considered unit. Failure mode and effect analysis (FMEA) was carried using qualitative information gathered from system's expert opinions. Fuzzy-complex proportional assessment (FCOPRAS) approach was integrated within FMEA to recognize the most critical failure causes associated with various subsystem/components.FindingsThe availability of the unit falls by 0.053% as the uncertainty level increases from ±15 to ±25% and further decreases to 0.323% as the uncertainty level increases from ±25 to ±60%. Failure causes, namely wearing in gears of gearbox (MST4), an impeller's cavitation and/or corrosion (CFP4), winding failure of electric motor (WS9), were recognized as the most critical failure causes with FCOPRAS final performance scores of 100, 100 and 100 and fuzzy combinative distance-based assessment (FCODAS) resultant assessment score of 0.5997, 1.1898 and 1.6135.Originality/valueJBLTO approach-based reliability results were compared with traditional particle swarm optimization-based Lambda–Tau (PSOBLT) and traditional fuzzy Lambda–Tau (FLT) approaches for confirming the downward trend in the system's availability. The ranking results of qualitative analysis are compared with the implementation of FCODAS technique. Sensitivity analysis was executed to evaluate the robustness of the proposed hybridized framework.
使用JBLTO, FCOPRAS和FCODAS方法进行性能优化的结构化框架
目的提出的混合框架为分析奶业中奶牛厂机组(PU)的失效行为提供了一种新的基于性能优化的范式。设计/方法/方法提出了一种新的基于模糊jaya的Lambda-Tau优化(JBLTO)方法的数学模型,用于计算考虑单元的各种可靠性指标。利用从系统专家意见中收集的定性信息进行故障模式和影响分析(FMEA)。在FMEA中集成了模糊-复杂比例评估(FCOPRAS)方法,以识别与各个子系统/组件相关的最关键故障原因。当不确定度从±15%增加到±25%时,该装置的可用性下降0.053%,当不确定度从±25%增加到±60%时,该装置的可用性进一步下降至0.323%。FCOPRAS最终性能得分分别为100分、100分和100分,模糊组合距离评价(FCODAS)综合评价得分分别为0.5997、1.1898和1.6135,结果表明,齿轮箱齿轮磨损(MST4)、叶轮空化和/或腐蚀(CFP4)、电动机绕组失效(WS9)是最关键的失效原因。将基于独创性/valueJBLTO方法的可靠性结果与传统的基于粒子群优化的Lambda-Tau (PSOBLT)方法和传统的模糊Lambda-Tau (FLT)方法进行比较,以确定系统可用性的下降趋势。将定性分析的排序结果与FCODAS技术的实施结果进行了比较。采用敏感性分析来评价所提出的杂交框架的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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
×
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