Data-T-Rex 2

The light metal industry is facing a fundamental transformation: higher recycling rates, increasing demands on product quality and resource efficiency call for new materials and more flexible production processes. This is where the Data-T-Rex 2 research project comes in. Led by the LKR Leichtmetallkompetenzzentrum Ranshofen at the AIT Austrian Institute of Technology, the project digitally links materials, production processes and materials analysis to develop optimised recycled alloys and adaptive process chains. The focus is on aluminium, magnesium and titanium alloys, as well as innovative analysis, simulation and AI methods. The project is funded by FTI-OÖ, the Province of Upper Austria.

Increased recycling poses new challenges for the process industry

The increased use of recycled materials is a key component of more sustainable light metal production. At the same time, higher and fluctuating proportions of recycled material present new challenges, as variations in the composition of the recycled fractions can lead to changes in the properties of the raw material. For industrial processing, this means that established process parameters do not always result in consistent material and component properties.

There is therefore a need for robust alloy designs that enable forming behaviour that is as consistent as possible and reproducible component properties, even with varying raw materials. At the same time, production processes must become more flexible and be able to respond to changes in the material.

A key to achieving this lies in a better understanding of the interactions between material, process and the resulting properties. Phenomena in metal physics, such as recrystallisation, texture, phase formation and residual stresses, have a significant influence on how a material behaves during processing. Analytical methods and simulation provide important information about the underlying material structures and how these are altered by the process conditions.

Data-T-Rex 2: Digitally linking materials, processes and analysis

This is precisely where Data-T-Rex 2 – data-driven optimisation of the metallurgical processes of recrystallisation and texture in recycled alloys – comes into play. The aim is to take a holistic digital view of the metallurgical process chain, in which data from material development, production and materials analysis are brought together and used for optimisation.

The central research question is: How can recycled materials be developed and processed in such a way that efficient, stable and high-quality production is possible despite varying material properties?

To this end, the project addresses three closely interlinked areas of research:

Materials and Processes

The research covers, amongst other things, recycled aluminium alloys as well as magnesium, titanium and nanoeutectic alloys. The focus is on their behaviour throughout various process chains. On this basis, the aim is to develop materials and design process steps in such a way that they are better suited to recycled materials.

Flexible and adaptive production processes are of particular importance here. In future, they should be able to react immediately to fluctuations, for example in the chemical or mechanical properties of materials. This will ensure stable production processes whilst reducing scrap volumes.

Analysis and Simulation

Another key focus is on the further development of digital methods for the characterisation and interpretation of materials. This includes, amongst other things, improvements in EBSD analysis and DSC evaluation, as well as the simulation of material behaviour taking into account texture development.

The combination of experimental analysis and simulation enables a more detailed understanding of the relationships between microstructure, process control and material properties. This knowledge, in turn, forms the basis for the targeted further development of alloys and production processes.

Digitalisation and Artificial Intelligence

The information obtained is to be consolidated within a digital process landscape. To this end, the existing LKR Dataspace will be further developed and, amongst other things, expanded to include data from the testing centre.

In addition, research is being carried out into how synthetic data can be generated and utilised for AI-based process analyses. The aim is to establish stronger links between sensor data, digital material information and analysis results. In the long term, such systems could, for example, help to proactively optimise production processes, detect material fluctuations at an early stage or predict maintenance requirements.

LKR brings extensive research expertise to bear across the entire process chain

A particular strength of the LKR Leichtmetallkompetenzzentrum Ranshofen within this project lies in the interdisciplinary integration of materials science, metallurgy, forming technology, simulation and digitalisation. With its comprehensive infrastructure and many years of expertise, the LKR is able to replicate key processing steps for aluminium, titanium and magnesium alloys on a semi-industrial scale – from continuous casting through various forming processes to targeted heat treatments. This is complemented by modern methods for the characterisation and evaluation of light metals, as well as long-standing expertise in metallurgy, materials science, and casting and forming technology. The LKR thus possesses the necessary expertise to investigate materials and processes holistically, develop them further in a targeted manner and evaluate them in terms of their properties and performance.

This understanding of materials and processes is specifically combined with digital expertise in Data-T-Rex 2. This includes sensor technology, machine learning, image processing, digital materials analysis and simulation.

The potential offered by this combination had already been demonstrated in the predecessor project, Data-T-Rex. Among other things, AI methods for microstructure characterisation were developed, texture simulations were made possible, new alloy concepts were investigated and various forming processes were analysed. At the same time, plant was equipped with sensor technology and, with LKR Dataspace, the foundations were laid for a digital process and analysis platform.

With Data-T-Rex 2, this approach is being consistently pursued and tailored to the requirements of a more circular light metals industry.

Thinking about recyclability and digitalisation together

Carina Schlögl, authorised representative at LKR, emphasises the importance of a holistic approach: “Data-T-Rex 2 brings together two key future themes in the light metals industry: the increased use of recycled materials and the digitalisation of production. Particularly when recycling rates are higher, we have to deal with greater fluctuations in material properties. The digital integration of material, process and analysis provides the basis for adapting processes in a more targeted manner and utilising recycled materials more reliably. We find the combination of metallurgical expertise with sensor technology, simulation and artificial intelligence particularly valuable – this enables us not only to gain new insights, but also to develop concrete solutions for more resource-efficient and flexible production.”

From research to industrial application

The expected results are intended to benefit both research and industrial practice. The focus is on toolkits for the development and processing of future materials, which will enable new recycled materials to be developed more quickly and production processes to be adapted more flexibly to different input materials.

Furthermore, the digital integration of the process chain is intended to help use resources more efficiently, reduce CO₂ emissions and, at the same time, improve product quality. By utilising process and material data, for example, interactions along the process chain can be better recognised and opportunities for optimisation identified. This also supports applications such as predictive maintenance and automated process adjustments.

A further aim of the project is to demonstrate the opportunities that digitalisation and AI open up for the metalworking industry – particularly for small and medium-sized enterprises, which are increasingly faced with the challenge of producing in a more sustainable yet competitive manner.

Funding information: FTI OÖ, Province of Upper Austria, project number Wi-2025-212607/16-FrJ