Rexonni B Lagare, M Ziyan Sheriff, Marcial Gonzalez, Zoltan Nagy, Gintaras V Reklaitis
{"title":"连续式干法造粒生产线状态监测系统模块化开发综合框架。","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":"{\"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}","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}
A Comprehensive Framework for the Modular Development of Condition Monitoring Systems for a Continuous Dry Granulation Line.
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.