CondOR-EEE

Project description

Aluminium alloys are an important material for lightweight parts in the automotive and aerospace industry and in the energy sector. Their mechanical properties depend on a complex thermomechanical process chain, including homogenization and heating for extrusion or rolling. Currently key quality parameters can only be measured on the final product, which makes it difficult to optimize processes and to reduce reject rates.

Within the CondOR-EEE project a method for in-situ measurement of electrical conductivity is developed. This allows data acquisition during key steps of the production process. The conductivity data are used as a complete “fingerprint” of the material, changes in the structure of the material can thus be determined in real-time and process adjustments can be made.

The main challenge is the interpretation of electrical conductivity in the presence of changes in temperature and during complex metallurgical processes. Based on a proof-of-concept from an earlier project, the technology will be further developed to include all process parameters and to generate a digital representation of the material. This will be the basis for data-driven, adaptive process control.

Project objectives and technical innovation

CondOR-EEE aims at developing methods for the acquisition and interpretation of electrical conductivity data during heat treatments of aluminium. These data will enable predictions about the quality of the final product.

Key activities include:

• Development of in-situs sensor system that can continuously measure the electrical conductivity of aluminium during thermomechanical processes.
• Implementation of machine learning methods to deal with the influence of varying temperature and other sources of signal noise and to obtain a robust characterization of the material in the form of a “fingerprint”.
• Merging of measurement data with process parameters (temperature, processing speed, …) to obtain models that link quality to process and material parameters.

The goal is to increase the TRL of the technology from 2/3 to 4 and to pave the way for real-time process optimization based on such measurement data.

Application & benefits for the market, environment, and research

The resuls of the CondOR-EEE project will enable aluminium processing plants to determine material properties in real-time and to draw conclusions about variations of the process. Data-driven models will predict the material parameters of the finished products and reduce reject rates. The robustness and reproducibility of processes will increase, leading to a more efficient use of valuable raw materials and energy. In the long term the developed sensor technology will enable real-time feedback, thus reducing the need for end-of-line (possibly destructive) testing.