UrBC, Yekaterinburg, September 19, 2019. ChelPipe Group introduced a special digital solution to improve its steel-smelting process. Machine-learning technology was relied upon to develop and launch a ‘steel-smelter’s support algorithm’ that makes it possible to control the composition of steel and minimize losses related to the raw material consumption.

According to the Group’s press service, the company is expected to save RUB 50m by the end of 2019 and as much as RUB 100m and more in the following years. The solution has been launched at the electric furnace-melting department Iron Ozone 32 at the Group’s Pervouralsk New Pipe Plant (PNTZ).

The solution relies on AI which learns from the earlier input on the steel-smelting process, comes up with a forecast, and produces recommendations as the composition that would be most suitable for making a particular type of steel. Big Data technologies were used to design a model of how production factors can affect/prove detrimental to the quality of pipe stock. The model can advise a steel-smelter on a certain combination of slag-forming and ferrous materials to obtain the steel with the necessary chemical composition parameters online. Besides, the algorithm lets you optimize the cost of the ferrous materials used in the production process. The steel-smelters can also control the chemical composition of steel and analyze the production data online.