Investigation of Processing Parameters on the Mechanical and Physical Properties of AA6061 Chip-Based Forged Parts Using MLR-GA Method

Abstract

Solid-state recycling of aluminium offers an energy-efficient and environmentally friendly alternative to conventional melting-based methods. This study investigates the influence of processing parameters on the mechanical and physical performance of AA6061 chip-based forged components using Multiple Linear Regression (MLR) and Genetic Algorithm (GA) techniques. Aluminium chips produced by high-speed milling were consolidated through hot press forging at temperatures of 450°C, 500°C, and 550°C, with holding times of 60, 120, and 180 minutes. Tensile testing was conducted to assess the mechanical properties, with the ultimate tensile strength (UTS) selected as the main response variable. In addition, density testing was carried out to evaluate the physical properties of the forged samples. The MLR models successfully established correlations between forging parameters and UTS, while GA optimization identified the most favourable conditions for superior mechanical properties. The results showed that a higher forging temperature of 550°C and a longer holding time of 180 minutes improved the bonding between chips, resulting in higher UTS. The highest UTS was achieved at 550°C, 180 minutes, and a chip surface area of 73.77 mm². These findings highlight the potential of optimized solid-state recycling to produce high-quality aluminium components, thereby supporting sustainable manufacturing and efficient resource utilization in materials engineering.