Determination and control of bonding properties in aluminum composites in the combination of compound casting and forming

• Applicants: Professor Dr.-Ing. Noomane Ben Khalifa; Professor Dr.-Ing. Wolfram Volk
• Subject Area: Primary Shaping and Reshaping Technology, Additive Manufacturing
• Term: from 2017 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 329779887

The production of structural composites based on aluminum materials is subject of current lightweight design developments in industry and research. The combination of different technological material properties in a single part leads to an increasing range of applications for lightweight construction materials. Knowledge of bonding properties inside the specimen is essential for a load-related design of the composites. Therefore, scientific work has been done to analyze the bonding properties reached depending on process conditions in the production of composites using primary forming and forming technology.Processing of semi-finished products consisting of a metallurgical compound for warm and cold extrusion forming technology is new and not yet investigated. Therefore, the basic correlations in the change of bonding properties of casting composites due to massive forming processes are investigated in this research project. The aim of the research project is a continuous prediction and modification concerning the bonding quality of two different aluminum alloys along the process chains compound casting - cold extrusion forming and compound casting - warm extrusion forming. Casting composites are produced in sand mold and permanent mold casting.Within the framework of the research project composite billets are produced by discontinuous casting experiments, followed by forming under different process conditions. Bonding properties are analyzed using metallographic and mechanical test methods after each process step. Determining the bonding strength enables a continuous quantification of the bonding properties, which should be transferred into a prediction model. The comparison and analysis of experimental (measured) and simulated results leads to the identification of cause-and-effect relationships for the investigated process chains.

• DFG Programme: Research Grants