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Retrofitting equipment for efficient use of variable feedstock in metal making processes

Periodic Reporting for period 1 - REVaMP (Retrofitting equipment for efficient use of variable feedstock in metal making processes)

Berichtszeitraum: 2020-01-01 bis 2021-06-30

In the European process industries large amounts of energy and resources are used to produce millions of tonnes of materials each year. Especially in metal making processes, metallic scraps from end of life goods are recycled and used as secondary raw materials in the processes. Usage of scrap is both ecologically and commercially beneficial, since it reduces the depletion of natural resources like virgin ores and avoids landfills with waste material. Today even more important is that the energy consumption and the CO2 emissions of the reduction processes of metal ores can be reduced or even totally avoided when using recycled materials as feedstock. However, the metal production facilities are facing an increasing variability in material and energy feedstock.

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 the first 18 Months of the project, the challenges for the project were clearly defined and the retrofitting tools and methodologies to be applied in the second part of the project were developed and prepared.

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.
During the first part of the project, already important steps for a significant progress beyond the state of the art have been performed, especially regarding the development of the novel neutron and LIBS sensors for in-line analysis of the metal scrap composition, and the engineering of a scrap preheating system using waste derived fuels, but also regarding modelling of the scrap properties by means of statistical methods, and the development of analytical and data-based models for monitoring and prediction of the process behaviour

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.
Figure 1: Overview on objectives, methods and expected results of the REVaMP project
Figure 2: Overview on retrofitting tools and applied methods in the REVaMP project