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Zero Defect Manufacturing for Thermo-dynamical Processes

The strategic orientation of the LKR in the coming years is fundamentally shaped by two aspects: Digitalization and decarbonization, where digitalization can make a very significant contribution to climate protection by helping to increase productivity while keeping costs low and reducing CO2-emissions.

Thus, the manufacturing industry is undergoing a profound transformation to make production more efficient with new, digital solutions along the manufacturing chain. "Zero Defect Manufacturing" is a general term that is intended to enable defect-free products and processes in a wide variety of production steps.

The FFG project "Zero Defect Manufacturing" (ZDM) aims to realize the methodology of defect prevention for specific industrial manufacturing processes, which often represent complex, thermodynamic processes. The consortium leader is PROFACTOR GmbH, other project partners are Swarovski, FACC, FH OÖ, AIT Austrian Institute of Technology (Center for Digital Safety & Security) and MESA Electronics.

The project will demonstrate how data-driven modeling can be used in combination with physical models to move from current "recipe-based" processes to more flexible processes that are based on the actual state of a component. The pre-requisite for the ZDM logic in all projects is the acquisition and processing of in-situ sensor signals, which form the basis for controlling the processes.  

The project focuses on three use cases: the curing of carbon fiber composite components in autoclaves, the surface treatment of decorative products and the heat treatment of aluminum.

For the specific area of aluminum production, a close correlation between heat treatment conditions, processability (e.g. extrusion, rolling, forging) and the properties of the end-product has been demonstrated at the LKR in preliminary scientific work [1, 2]. By optimizing the heat treatments, defects such as edge cracks or insufficient surface quality can be reduced. For this optimization, an understanding of the microstructure is crucial, which has so far been obtained by ex-situ-methods such as microscopy or electrical conductivity measurements at various points during the heat treatment (after quenching the material). Conductivity measurements provide information about the microstructure, since alloying elements dissolved in the Al-metal-matrix have a very strong influence on conductivity, whereas these elements in the form of precipitates have practically no influence on electrical conductivity [3].

Fig. 1 outlines those heat treatment processes which are typically carried out in the production of wrought Al-alloys. Sometimes, solution heat treatment is performed after extrusion (or hot or cold rolling). For all heat treatment steps, process control by means of in-situ conductivity measurement is basically conceivable.

Fig.1: Typical heat treatment processes on wrought aluminum alloys

From the temperature range in which changes in electrical conductivity occur, conclusions can also be drawn about the nature of the phases. In principle, this is analogous to DSC measurements (calorimetry), however, the conductivity measurement can also be carried out directly on real components during production.

In summary, the overall goals in this project are:

  1. Implementation of sensors suitable for direct integration into the manufacturing process to obtain information about the current state of the process or product.
  2. Development of simulation tools that bridge the gap between raw sensor signals and a higher-level characterization of product or process condition. Simulation tools will also provide the framework for storing information about each part "as manufactured," creating a digital twin of each manufactured part.
  3. Development of machine learning (AI) methods to improve production processes in terms of performance indicators such as quality (scrap rate), energy consumption, and productivity by integrating information from sensors, simulation, and other production steps, including quality control at the end of the production line.


[1] Österreicher, J., Schiffl, A., Falkinger, G., & Bourret, G. R. (2016, March). Microstructure and mechanical properties of high strength Al–Mg–Si–Cu profiles for safety parts. In IOP Conf. Ser.: Mater. Sci. Eng (Vol. 119, p. 012028).

[2] Österreicher, J. A., Kumar, M., Schiffl, A., Schwarz, S., & Bourret, G. R. (2017). Secondary precipitation during homogenization of Al-Mg-Si alloys: Influence on high temperature flow stress. Materials Science and Engineering: A, 687, 175-180.

[3] Optimisation of Al-Mg-Si extrusion-alloys for application in the automotive industry. Master thesis, TU Vienna, 2020.


Funded by the Federal Ministry for Climate Protection, Environment, Energy, Mobility, Innovation and Technology (BMK) and the Austrian Research Promotion Agency (FFG).