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Severstal uses AI to Boost Productivity at Cherepovets Steel Mill

Steel News - Published on Fri, 26 Jun 2020

Image Source: Severstal AI
A team of specialists from Severstal Digital, working with experts in flat rolled products from the Cherepovets Steel Mill have successfully increased the productivity of a machine learning model that controls the speed of the Mill’s continuous pickling line NTA-3. Adelina, a digital model in use at Severstal’s continuous pickling line since November 2019, has now been joined by Ruban, a new artificial intelligence agent based on a deep reinforcement learning algorithm. Both products were developed by Severstal in-house using open source applications. Adelina and Ruban now work in parallel with one another; Adelina controls the speed of the unit, and Ruban adjusts the speed to achieve optimal results. This partnership has made the production process more flexible and secure, as the model and agent are able to adjust the speed of the unit every second and respond instantly to any unforeseen situation.

Ruban differs from classic machine learning models, learning not just from historical data, but independently, by exploring the digital twin of NTA-3. The operating speed at the unit largely depends on the parameters of the passing steel strip – the length, width and thickness of the roll, its steel grade and temperature, among other factors. Ruban learns from combinations of different parameters, specifically created for it by a generative adversarial network, which uses two neural networks to generate new data. It also sets a production plan and creates unique situations for training purposes. For effective learning, the agent was assigned a training system based on rewards and penalties; Ruban experiments to find a solution where the reward amount surpasses the penalties as far as possible.

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Posted By : Yogender Pancholi on Fri, 26 Jun 2020
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