Periodic Reporting for period 1 - REVaMP (Retrofitting equipment for efficient use of variable feedstock in metal making processes)
Reporting period: 2020-01-01 to 2021-06-30
To cope with this challenge, existing metal production plants need to be retrofitted with appropriate sensors for scrap analysis and furnace operation, to cope with the varying conditions of the feedstock regarding materials and energy.
Furthermore, the selection of the optimal feedstock in terms of material and energy efficiency has to be improved by application of appropriate process control and decision support tools. Also solid scrap preheating systems can increase the energy efficiency of the melting processes. To monitor and control the process behaviour in an optimal way, model-based software tools have to be developed and applied.
The main objective of the REVaMP project is to develop, adapt and apply novel retrofitting technologies to cope with the increasing variability and to ensure an efficient use of the feedstock in terms of materials and energy. This will be exemplarily demonstrated within three different use cases from the metal making industry. Due to the industrial relevance, the use cases were chosen from electric and oxygen steelmaking, aluminium refining and lead recycling. The performance of the different technologies will be assessed, and the benefits will be quantified.
Figure 1 gives an overview on the challenges and objectives for the metal making industries, the methods which shall be applied within the different demonstration cases and the expected results. The applied methods and tools are further broken down in Figure 2.
In detail, the economic, technological and regulatory challenges for the different use cases in the metal making industry were identified. The physical-chemical specifications of material feedstocks for acceptance as input materials in metal making processes, as well as the specifications of waste derived fuels as energy feedstock for application in scrap preheating within the aluminium refining process were defined. Also the requirements for the sensor and equipment installations and their expected performance in the different use cases were set up. Also, the requirements for process models, monitoring and control systems were defined, and the process data to be collected for their industrial validation were set up. Finally, the scope for Life Cycle Analyses (LCA) for the processes within the different use cases was defined.
The development and adaptation of process models covered the modelling of
• the operational input conditions in terms of material and energy feedstock
• the process behaviour and performance of the metal making processes within the different industrial use cases
• the material flow within the different industrial use cases
The models were prepared for application within process monitoring and control tools. Their development was started regarding the production processes in the three industrial use cases:
• Process monitoring and control tools based on enhanced process models for the different melting furnaces
• Decision support systems for optimisation of charge and alloy material mixes
Furthermore, the development of AI-based optimisation tools for steelmaking and aluminium furnaces focussing on the energetic performance was started. Also, a first prototype for a model-based software service to support requests for prediction and optimization was set up.
The material flow analysis serves as basis for the LCA to be applied in the final evaluation work.
In parallel, the development work for the sensor technologies and plant components for installation in the metallurgical plants of the different use cases was started. The following sensors for material characterisation and a scrap preheating system were engineered, set up, tested in laboratory scale and prepared for installation within the use cases:
• a neutron activation analysis sensor for bulk chemical analysis of metal scrap
• a smart LIBS sensor system for surface chemical analysis of metal scrap
• temperature and gas composition sensors for the aluminium melting process, as well as a quality sensor for the produced aluminium melt
• design and engineering of an aluminium scrap preheating system using waste derived fuels
Finally, a dissemination and exploitation plan was drafted and first dissemination actions like the implementation of a project web site and a project flyer were performed.
The contribution of the project to the expected impacts is still relevant and can be described as follows:
• the energy efficiency of the involved processes shall be increased significantly, depending on the respective use cases between 5 – 25 %.
• the expected improvements in resource efficiency strongly vary depending on the use case. They are on the lower range of 1 % for the liquid steelmaking process, and shall reach about 20 % for aluminum production.
• The GHG emissions are expected to be decreased by 2 – 30 %. Especially those processes which strongly depend on fossil fuels, as oxygen steelmaking or alumium refining with gas-fired furnaces, are expected to reach higher savings.
• Reduced OPEX costs and increased productivity are closely connected with the increased use of low-quality scrap and a reduction of out-of-spec production by a better control of the charge material properties.
As the implementation phase of the retrofitting solutions has not yet started, so far no figures can be provided to which extend the savings listed above can be reached. A more detailed comparison of the already achieved impact in comparison to the set targets will be provided in the next periodic report.