Towards Automated Generation of Function Models from PIDs

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Although function model has been widely applied to develop various operator decision support systems, the modeling process is essentially a manual work, which takes significant efforts on knowledge acquisition. It would greatly improve the efficiency of modeling if relevant information can be automatically retrieved from engineering documents. This paper investigates the possibility of automated transformation from PIDs to a function model called MFM via AutomationML. Semantics and modeling patterns of MFM are established in AutomationML, which can be utilized to convert plant topology models into MFM models. The proposed approach is demonstrated with a small use case. Further topics for extending the study are also discussed.

Original languageEnglish
Title of host publicationProceedings of 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation
PublisherIEEE
Publication dateSep 2020
Pages1081-1084
Article number9212146
ISBN (Electronic)9781728189567
DOIs
Publication statusPublished - Sep 2020
Event25th IEEE International Conference on Emerging Technologies and Factory Automation - Virtual event, Vienna, Austria
Duration: 8 Sep 202011 Sep 2020
http://www.ieee-etfa.org/2020/

Conference

Conference25th IEEE International Conference on Emerging Technologies and Factory Automation
LocationVirtual event
Country/TerritoryAustria
CityVienna
Period08/09/202011/09/2020
Internet address
SeriesIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume2020-September
ISSN1946-0740

Keywords

  • Automated model generation
  • AutomationML
  • Functional modeling
  • MFM
  • PIDs

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