Journal of Manufacturing and Materials Processing (Aug 2024)
Efficiency and Microstructural Forecasts in Friction Stir Extrusion Compared to Traditional Hot Extrusion of AA6061
Abstract
Conventional aluminum recycling consumes a substantial amount of energy and has a negative impact on secondary alloys. To address this challenging topic, Friction Stir Extrusion has been patented, which represents an innovative solid-state recycling technique that enables the direct extrusion of components from recyclable materials. In recent years, developing simulation models for Friction Stir Extrusion has become essential for gaining a deeper understanding of its underlying physics. Simultaneously, control of the microstructure evolution of extruded profiles is required, as it has a considerable influence on mechanical properties. This research involves a single Lagrangian model, adapted for both the FSE and the traditional hot extrusion processes. The simulations explored various rotational speeds and feed rates, revealing significant effects on grain size and bonding quality. To this model were applied different sub-routines, to investigate the impact of the FSE process with respect to the traditional hot extrusion process in terms of energy demands, quality and microstructure of the extruded pieces. The findings demonstrated that optimal grain refinement occurs at intermediate rotational speeds (600–800 rpm) combined with lower feed rates (1 mm/s). The energy analyses indicated that FSE requires lower total energy compared to traditional hot extrusion, primarily due to the reduced axial thrust and more efficient thermal management. As a result, it was possible to ensure the ability of the developed simulative model to be fully adapted for both processes and to forecast the microstructural changes directly during the process and not only at the end of the extrusion. The study concludes that FSE is a highly efficient method for producing high-quality extruded rods, with the developed simulation model providing valuable insights for process optimization. The model’s adaptability to various starting materials and conditions highlights its potential for broader applications in extrusion technology.
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