PRIM-ROCK addresses process efficiency through a multifaceted strategy addressing industrial processes from input to output, supported by an ambitious digital framework and transversal supporting activities. In particular, advanced techniques for the pre-processing of the raw material will be deployed to enhance its efficiency according to the requirements of the process, supplemented by simulations and decision support systems to increase the operational limits of flexibility in the feedstock domain. Additionally, the process intensification component of the project will design, develop, and validate innovative and efficient processes, as well as optimizing the existing ones. The aim is to develop a portfolio of technologies to a higher resource efficiency and lower level of GHG emissions of extractive industries. The project will focus on improving the resource efficiency of the calcination and roasting processes, that are commonly used in the mineral and cement industries. To this end, process simulations in collaboration with AI data-driven models will be utilized and a digital twin for each process will be developed. Finally, waste reduction and re-utilization strategies will be investigated targeting to the real-time processes’ adjustment capabilities to feedstock changes and tighter processing control solutions. All these components will be supplemented by transversal supporting activities, such as technoeconomic assessment, LCA, standardization etc. The PRIM-ROCK solutions will be demonstrated in 3 different ASPIRE sectors, namely Minerals (magnesite, laterite), Cement (limestone) and Non-ferrous metals (sphalerite, chalcopyrite). The consortium is composed of 7 SMEs along with 6 RTDs, 3 universities and 5 large enterprises, working together to achieve over 30% resource efficiency enhancement in each use-case, 770ktCO2 averted, productivity increase in the range 9-16% and more that 1,360 new jobs by 2033.

COGNIPLANT project will develop and demonstrate an innovative approach for the advanced digitization and intelligent management of the process industries. This approach will be based on a novel vision to data monitoring and analysis, that will make the most of the latest developments on advanced analytics and cognitive reasoning, coupled with a disruptive use of the Digital Twin concept to improve Production plants’ operation performance by up to 68% in real time control of the productive environment, 65% in quality control of the final products and 70 % in response time to uncontrolled incidents. The concept will be implemented by four end-users from four different SPIRE industries, one chemical industry in Austria, one aluminum refinery in Ireland, one concrete manufacturing industry in Italy and one metal industry in Spain. The COGNIPLANT solution will provide a hierarchical monitoring and supervisory control that will give a comprehensive vision of the plants’ production performance as well as the energy and resource consumption. Advanced data analytics will be applied to extract valuable information from the data collected about the processes and their effect on the production plant’s overall performance enabling to design and simulate operation plans in digital twin models based on the conclusions. As a result, optimal operation plans will be obtained that will improve the performance of those cognitive production plants. In addition, the project will demonstrate the positive impact derived from the implementation of COGNIPLANT solution that will allow industries reducing their CO2 emissions up to 20%. A training strategy will be designed to provide a comprehensive framework for the dissemination of the project outcomes and a clear understanding of the new solution for the employees of the SPIRE sectors.