Artificial intelligence services in steel production - On premises and in the cloud

Sonja Strasser, Gerald Hohenbichler, Manuel Sattler, Petra Krahwinkler, Johann Reidetschlaeger

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

1 Citation (Scopus)


Physics-based metallurgical models have been used for decades in the steel industry. Advanced methods of machine learning and data sciences allow combining the strength of pure data models and proven physics models and exploiting their benefits. Expert know-how in steel is being integrated with data science expertise to provide the next level of digital services for the metals industry. This paper focuses on practical examples how to use artificial intelligence in steel production to gain deeper insight, develop new control schemes, find root causes, improve deviation forecasting, and to optimize operations, quality results and predictive maintenance.

Original languageEnglish
Title of host publicationProceedings of the Iron and Steel Technology Conference, AISTech 2020
PublisherIron and Steel Society
Number of pages9
ISBN (Electronic)9781935117872
Publication statusPublished - 2020
EventAISTech 2020 Iron and Steel Technology Conference - Cleveland, United States
Duration: 31 Aug 20203 Sept 2020

Publication series

NameAISTech - Iron and Steel Technology Conference Proceedings
ISSN (Print)1551-6997


ConferenceAISTech 2020 Iron and Steel Technology Conference
Country/TerritoryUnited States


  • Artifical Intelligence
  • Cloud-based services
  • Predictive maintenance
  • Process control
  • Process optimization


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