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

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

doi:10.33313/380/209

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 proceedings › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

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 language	English
Title of host publication	Proceedings of the Iron and Steel Technology Conference, AISTech 2020
Publisher	Iron and Steel Society
Pages	1936-1944
Number of pages	9
ISBN (Electronic)	9781935117872
DOIs	https://doi.org/10.33313/380/209
Publication status	Published - 2020
Event	AISTech 2020 Iron and Steel Technology Conference - Cleveland, United States Duration: 31 Aug 2020 → 3 Sept 2020

Publication series

Name	AISTech - Iron and Steel Technology Conference Proceedings
Volume	3
ISSN (Print)	1551-6997

Conference

Conference	AISTech 2020 Iron and Steel Technology Conference
Country/Territory	United States
City	Cleveland
Period	31.08.2020 → 03.09.2020

Keywords

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

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10.33313/380/209

Cite this

Strasser, S., Hohenbichler, G., Sattler, M., Krahwinkler, P., & Reidetschlaeger, J. (2020). Artificial intelligence services in steel production - On premises and in the cloud. In Proceedings of the Iron and Steel Technology Conference, AISTech 2020 (pp. 1936-1944). (AISTech - Iron and Steel Technology Conference Proceedings; Vol. 3). Iron and Steel Society. https://doi.org/10.33313/380/209

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title = "Artificial intelligence services in steel production - On premises and in the cloud",

abstract = "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.",

keywords = "Artifical Intelligence, Cloud-based services, Predictive maintenance, Process control, Process optimization",

author = "Sonja Strasser and Gerald Hohenbichler and Manuel Sattler and Petra Krahwinkler and Johann Reidetschlaeger",

note = "Publisher Copyright: {\textcopyright} 2020 by the Association for Iron & Steel Technology.; AISTech 2020 Iron and Steel Technology Conference ; Conference date: 31-08-2020 Through 03-09-2020",

year = "2020",

doi = "10.33313/380/209",

language = "English",

series = "AISTech - Iron and Steel Technology Conference Proceedings",

publisher = "Iron and Steel Society",

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Strasser, S, Hohenbichler, G, Sattler, M, Krahwinkler, P & Reidetschlaeger, J 2020, Artificial intelligence services in steel production - On premises and in the cloud. in Proceedings of the Iron and Steel Technology Conference, AISTech 2020. AISTech - Iron and Steel Technology Conference Proceedings, vol. 3, Iron and Steel Society, pp. 1936-1944, AISTech 2020 Iron and Steel Technology Conference, Cleveland, United States, 31.08.2020. https://doi.org/10.33313/380/209

Artificial intelligence services in steel production - On premises and in the cloud. / Strasser, Sonja; Hohenbichler, Gerald; Sattler, Manuel et al.
Proceedings of the Iron and Steel Technology Conference, AISTech 2020. Iron and Steel Society, 2020. p. 1936-1944 (AISTech - Iron and Steel Technology Conference Proceedings; Vol. 3).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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T1 - Artificial intelligence services in steel production - On premises and in the cloud

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AU - Hohenbichler, Gerald

AU - Sattler, Manuel

AU - Krahwinkler, Petra

AU - Reidetschlaeger, Johann

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Artifical Intelligence

KW - Cloud-based services

KW - Predictive maintenance

KW - Process control

KW - Process optimization

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M3 - Conference contribution

AN - SCOPUS:85092307957

T3 - AISTech - Iron and Steel Technology Conference Proceedings

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EP - 1944

BT - Proceedings of the Iron and Steel Technology Conference, AISTech 2020

PB - Iron and Steel Society

T2 - AISTech 2020 Iron and Steel Technology Conference

Y2 - 31 August 2020 through 3 September 2020

ER -

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

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Keywords

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