The proposed slag raking system will employ automated sensor and image processing as well as deep learning to better identify and remove slag from molten steel, an operation that requires precision and consistency, The Bay Observer said.

The project has received a CA$300,000 Applied Research and Development Grant from the National Sciences and Research Council of Canada, as well as support from Dofasco and Next Generation Manufacturing Canada.

“We believe in the collaboration required to achieve a world’s first for digitization at a ladle metallurgy facility,” Tony Valeri, vice president of corporate affairs for ArcelorMittal Dofasco, said, according to The Bay Observer. “The Mohawk College team’s contribution for an imaging and deep learning–based automated system is a critical component of our larger project portfolio.”

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