SMART TWIN LMF 4.0
The new project of Duferco Travi e Profilati Group, to equip the ladle furnace of San Zeno Naviglio with a Twin LMF solution
Smart Twin LMF 4.0 is a project aimed at creating a Twin LMF solution for the ladle furnace of the San Zeno Naviglio plant, adopting advanced technological principles in equipment, drives and sensors and advanced integration between supervision and control systems of process.
The project came into existance from the desire to increase the competitiveness and efficiency of the production process, reduce energy consumption, increase quality and reducing costs, combining the pre-existing melting furnace with a new plant in a physical and digital integration.
The project also obtained the approval of the Ministry of Economic Development, securing significant grants and subsidies at a subsidized rate, from the Sustainable Growth Fund and the Revolving Fund for Business Support and Investment in Research.
In 2019, the new ladle furnace was completed, thanks to the collaboration between Travi e Profilati di Pallanzeno of the Duferco TP Group and SMS Group and, between 2020 and the first months of 2021, the plant was tested and it completed the tests of performances that had been set at the start of the project.
ROBOT AND AUTOMATION
With the mechanical and industrial engineering department of the Università di Brescia, automatic systems have been developed and applied in order to help operators in carrying out the work, thanks to robots and automation tools, implemented to improve operations and plant safety.
DATA ANALYSIS
The TPP engineers of the Duferco group, in collaboration with Duferco Dev, have completed the development of a Digital Platform, integrated in the new system for the strategic analysis of data, which was then used by the Università di Brescia and the Università Cattolica, to guarantee high quality performance.
The development of process data collection systems, the creation of “big data” databases and analysis systems allow the optimization and increase of efficiency in the management of the production process.
Once the optimal process conditions have been reached, the last phase involves the development of advanced systems for control and simulation, based on algorithms and predictive systems. These will be able to optimize metallurgical processes both “off line”, therefore with analysis outside the production, and during the production itself, allowing the optimal management of any critical issues or anomalies.
