Rexonni B Lagare, M Ziyan Sheriff, Marcial Gonzalez, Zoltan Nagy, Gintaras V Reklaitis
{"title":"A Comprehensive Framework for the Modular Development of Condition Monitoring Systems for a Continuous Dry Granulation Line.","authors":"Rexonni B Lagare, M Ziyan Sheriff, Marcial Gonzalez, Zoltan Nagy, Gintaras V Reklaitis","doi":"10.1016/b978-0-323-85159-6.50257-8","DOIUrl":null,"url":null,"abstract":"<p><p>The development of condition monitoring systems often follows a modular scheme where some systems are already embedded in certain equipment by their manufacturers, and some are distributed across various equipment and instruments. This work introduces a framework for guiding the modular development of monitoring systems and integrating them into a comprehensive model that can handle uncertainty of predictions from the constituent modules. Furthermore, this framework improves the robustness of the modular condition monitoring systems as it provides a methodology for maintaining quality assurance and preventing unnecessary shutdowns in the event of some modules going off-line due to condition-based maintenance interventions.</p>","PeriodicalId":73493,"journal":{"name":"International symposium on process systems engineering","volume":"49 ","pages":"1543-1548"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923506/pdf/nihms-1870577.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International symposium on process systems engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/b978-0-323-85159-6.50257-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The development of condition monitoring systems often follows a modular scheme where some systems are already embedded in certain equipment by their manufacturers, and some are distributed across various equipment and instruments. This work introduces a framework for guiding the modular development of monitoring systems and integrating them into a comprehensive model that can handle uncertainty of predictions from the constituent modules. Furthermore, this framework improves the robustness of the modular condition monitoring systems as it provides a methodology for maintaining quality assurance and preventing unnecessary shutdowns in the event of some modules going off-line due to condition-based maintenance interventions.