ArcelorMittal Dofasco and Mohawk College have partnered to develop an automated system for slag-raking at the company’s Ladle Metallurgy Facility in Hamilton. Researchers from Mohawk College’s Sensor Systems and Internet of Things Lab will design and test an imaging and deep learning-based automated system for the identification and removal of slag, a byproduct of steelmaking.Researchers will work with steelmaking specialists to increase the accuracy of its slag-raking system by automating existing technologies and processes using IoT-driven sensor and image processing techniques. The team, led by Dr. Esteve Hassan, National Research Chair for IIoT Applications, will include experts in imagery, instrumentation and software, sensors, advanced manufacturing and process automation.The two-year project is funded by CAD 300,000 from the National Sciences and Research Council of Canada through an Applied Research and Development Grant. ArcelorMittal Dofasco is also investing in the project with the support of Next Generation Manufacturing Canada. The work is part of a large portfolio of digital transformation work currently being completed by ArcelorMittal Dofasco.Slag is produced when molten steel is separated from impurities. For every 300 tons of steel, approximately four tons of slag must be removed. Precision and consistency are an important part of the process. If too little slag is raked off, the quality of the final product is compromised. If too much molten steel is removed when the slag is raked off, the production efficiency is compromised.
ArcelorMittal Dofasco and Mohawk College have partnered to develop an automated system for slag-raking at the company’s Ladle Metallurgy Facility in Hamilton. Researchers from Mohawk College’s Sensor Systems and Internet of Things Lab will design and test an imaging and deep learning-based automated system for the identification and removal of slag, a byproduct of steelmaking.Researchers will work with steelmaking specialists to increase the accuracy of its slag-raking system by automating existing technologies and processes using IoT-driven sensor and image processing techniques. The team, led by Dr. Esteve Hassan, National Research Chair for IIoT Applications, will include experts in imagery, instrumentation and software, sensors, advanced manufacturing and process automation.The two-year project is funded by CAD 300,000 from the National Sciences and Research Council of Canada through an Applied Research and Development Grant. ArcelorMittal Dofasco is also investing in the project with the support of Next Generation Manufacturing Canada. The work is part of a large portfolio of digital transformation work currently being completed by ArcelorMittal Dofasco.Slag is produced when molten steel is separated from impurities. For every 300 tons of steel, approximately four tons of slag must be removed. Precision and consistency are an important part of the process. If too little slag is raked off, the quality of the final product is compromised. If too much molten steel is removed when the slag is raked off, the production efficiency is compromised.
