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Meeting 2022 TMS Annual Meeting & Exhibition
Symposium REWAS 2022: Automation and Digitalization for Advanced Manufacturing
Presentation Title Steel Production Efficiency Improvements by Digitalization
Author(s) Markus Schulte, Bill Emling
On-Site Speaker (Planned) Markus Schulte
Abstract Scope Digitalization supported by process knowledge drives the holistic improvement process for advanced steel producers. Four digital focus areas have been identified where digital applications are most impactful for an efficient steel production process: Asset Optimization, Product Quality, Energy and Sustainability as well as Production Planning. Applications in those areas are fed with data from sensors and automation systems, which are combined and preprocessed in a centralized data center. AI & ML help to find pattern in the data that allow forecasting of certain events before they occur. This makes it possible to react on undesired upcoming events and avoid their occurrence or mitigate their risk by suggested counter measures which can be directly executed via the automation systems. Several use case in those areas have been realized which increase efficiency and create value for steel producers.
Proceedings Inclusion? Planned:
Keywords Iron and Steel, Machine Learning,

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

AI/Data Mining in Materials Manufacturing
Audio Signal Processing for Quantitative Moulding Material Regeneration
Computational Methodology to Simulate Pyrometallurgical Processes in a Secondary Lead Furnace
Determining the Bubble Dynamics of a Top Submerged Lance Smelter
Development of Virtual Die Casting Simulator for Workforce Development
Digitalization for Advanced Manufacturing through Simulation, Visualization and Machine Learning
Digitalizing the Circular Economy (CE): From Reactor Simulation to System Models of the CE
Evolution of Process Models to Digital Twins
Factors to Consider when Designing Aluminium Alloys for Increased Scrap Usage
NOW ON-DEMAND ONLY - An Automated Recycling Process of End-of-life Lithium-ion Batteries Enhanced by Online Sensing and Machine Learning Techniques
Refractory Lifetime Prediction in Industrial Processes with Artificial Intelligence
Steel Production Efficiency Improvements by Digitalization

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