The “Dissemination of results of RFCS-Projects in the field of integrated intelligent manufacturing and public discussion of a roadmap in this field” (DISSI2M) workshop will be held at Sant’Anna School on May 22, 2019. The aim of the EU Research Fund for Coal and Steel (RFCS) 40 projects was to create an industry driven, sustainable and coordinated European Steel Skills Agenda and to tackle the challenges (economic, digital, technological developments and energy efficiency demands) that the steel sector is still facing. The objective of this workshop is to support the knowledge transfer and application of the results of numerous studies to formulate an ambitious mission: “producing steel with zero carbon in Europe by 2030”.

Since the first call for proposal was opened, the RFCS allocated funds for R&D and innovation to both coal and steel, bringing together industrial partners, SMEs, leading research centres and universities across the European Union, including the TeCIP (Communication, Information and Perception Technologies) Institute of Sant’Anna School.

Over the past two years, the partners defined concepts for mission-oriented and impact-focused approaches to address future global technology challenges. Research projects have been carried out on different aspects of steelmaking to improve the process performance in terms of resource optimization and environmental impact. This workshop is devoted to the analysis of the success rate of technology-based activities and the assessment of the main benefits from the industrial innovation strategies. The event also provides an opportunity for the ICT-COISP Centre researchers to highlight the outcomes of their holistic Digital Twins – Technology in the Steel Industry - that predict product performance across all critical properties.

Engineer Valentina Colla, as the ICT-COISP Centre coordinator, will present the “Optimization of the management of the process gases network within the integrated steelworks – GASNET”.

The project aims at minimizing the gas amount burned in torch, air emissions, environmental impact and costs. Forecasting models have been developed, with the aim of predicting the production and the demand of process off-gas inside the gas networks. Optimization strategies and Key Performance Indicators were defined to quantify the efficiency of the gas management during the exploitation of the Decision Support System.