Rolling is the last step in steelmaking and consists of the plastic deformation of steel ingots or semi-finished products. It is carried out in the so-called rolling mills, by means of the mechanical action of two rollers which, rotating at the same speed and in opposite directions, exert a pressure that achieves a reduction in the cross-section of the material. The process in each rolling line is unique, as each furnace, box, etc. is different. Given this casuistry of the industry, there is no standard predictive maintenance system for rolling lines and one has to be created ad hoc.

Due to the types of processes in the industry – hot or cold – and the great variability of the casuistry of the environment and of the production itself, the SMARTFAB project will use artificial intelligence to detect possible deviations in the processes, which will make it possible to detect failures in the plant before they occur. It also aims to predict the functioning of the systems, which will make it possible to know when plant maintenance is necessary and to plan it in advance. This will result in real-time, detailed knowledge of the state of the plant.

The research has investigated unique and innovative algorithms because a predictive maintenance system for a rolling mill line has never been created using the variables that will be used in this project. In particular, data from the furnace, the rolling mill and the billet at different stages of the process have been used.

The companies Celsa, Artelnics, T2C and EMIG are part of the project consortium coordinated by secpho. You can read more about the project here.

The project has been a beneficiary of the Next Generation EU funds channelled by the Ministry of Industry, Trade and Tourism within the support programme for Innovative Business Groups, whose objective is to digitise industry.

It is now being presented to the secpho ecosystem through an informative session, in which the terms of the research and the results obtained in this project will be made known.