Institute of Production Engineering and Machine Tools Research Current projects
Fatigue Strength Optimisation of Additively Manufactured Aluminium Components

Fatigue Strength Optimisation of Additively Manufactured Aluminium Components

E-Mail:  abdelmonaem@ifw.uni-hannover.de
Team:  Abdelmonaem, Abdallah
Year:  2025
Funding:  Deutsche Forschungsgemeinschaft - DFG
Duration:  01/2025 - 07/2027

Direct Energy Deposition-Arc (DED-Arc) enables the fast and efficient production of large, complex components. Additionally, this process can be used to extend existing components, such as in the variant production of cast components. However, process-induced shape deviations as well as structural inhomogeneities and porosities occur. This often leads to reduced mechanical load capacity, so that post-processing of the components or individual functional surfaces is needed.

For industrial application of additively manufactured aluminium parts, a deep understanding of the interactions between the DED-Arc process, heat treatment, machining, and deep rolling is essential to reliably achieve the required mechanical and technological properties.

 

Objectives

Of particular scientific interest is the interaction within the entire process chain and its influence on the subsurface properties of the components. The aim of the research project is therefore to optimise the local mechanical properties through a tailored process sequence, particularly to increase fatigue strength. This is especially relevant for structural components requiring certification, as it ensures that the required mechanical and technological properties are reliably achieved.

 

Benefits

  • Comprehensive understanding of the process chain for tailoring component properties
  • Increased fatigue strength of additively manufactured aluminium components
  • Broader applicability of the DED-Arc process for high-strength structural components

 

Approach

Experimental and numerical methods are combined to assess the effects of the process chain. Microstructure analyses, instrumented indentation tests, and computed tomography provide insights into the microstructure and porosity, while FEM simulations predict the influence of the individual processing steps. Empirical models are created to describe the relationships between process parameters, subsurface properties, and fatigue strength.

 

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Contact Abdallah Abdelmonaem via email at abdelmonaem@ifw.uni.hannover.de or by phone at +49 511 762 18387.