AI takes a closer look at steel materials
Global pricing pressure is pushing the German steel industry into crisis to an ever-increasing extent. One potential way out could be the implementation of more efficient production processes with the help of artificial intelligence (AI).14 Feb. 2020 Kai Tubbesing
The new MPV (Mechanical Properties Variability) application, designed to help steel manufacturers achieve greater efficiency, represents a joint development by the SMS digital digitization unit of the Düsseldorf-based plant manufacturer SMS Group and the Californian AI specialist Noodle.ai. The application makes use of artificial intelligence and machine learning to get a grip on the variability of mechanical material properties in steel production. This primarily involves aspects such as yield point, tensile strength and elongation: MPV detects patterns in the recorded process data and identifies the source of deviations. Based on this, it derives corresponding forecasts and recommendations.
Ultimately, the AI solution has the potential for substantial cost savings in steel production, including lower alloy component costs due to improved controls, or early detection of material below the tolerance specifications, that would otherwise have to be sold as second choice or be scrapped. The developers of the application report that one steel manufacturer already using MPV expects to save two million US dollars per year.
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