Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging.

Direct recycling of aluminum waste is crucial in sustainable manufacturing to mitigate environmental impact and conserve resources. This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. The experimental runs were designed using Full factorial and RSM via Minitab 21 software. RSM-ANN models were employed to examine the effect of factors and their interactions on response and to predict output, while GA-RSM and GA-ANN were used for optimization. The chips of different morphology were cold compressed into billet form and then hot forged. The effect of varying forging temperature (Tp, 450-550°C), holding time (HT, 60-120 minutes), and chip surface area to volume ratio (AS:V, 15.4-52.6 mm2/mm3) on ultimate tensile strength (UTS) was examined. Maximum UTS (237.4 MPa) was achieved at 550°C, 120 minutes and 15.4 mm2/mm3 of chip's AS: V. The Tp had the largest contributing effect ratio on the UTS, followed by HT and AS:V according to ANOVA analysis. The proposed optimization process suggested 550°C, 60 minutes, and 15.4 mm2 as the optimal condition yielding the maximum UTS. The developed models' evaluation results showed that ANN (with MSE = 1.48%) outperformed RSM model. Overall, the study promotes sustainable production by demonstrating the potential of integrating RSM and ML to optimize complex manufacturing processes and improve product quality.

The Effect of Solid-State Processes and Heat Treatment on the Properties of AA7075 Aluminum Waste Recycling Nanocomposite.

Direct solid-states, such as hot extrusion and equal channel angular pressing (ECAP), are alternative and efficient solid-state processes for use in recycling aluminium scrap. These processes utilise less energy and are eco-friendly. Ceramic particles such as ZrO2 are suggested as alternatives in the production of metal composites. This study investigated and optimised the effects of various parameters of reinforced ZrO2 nanoparticles on the mechanical and physical properties via response surface methodology (RSM). These parameters were the volume fraction (VF), preheating temperature (T), and preheating time (t). The effects of these parameters were examined before and after the heat treatment condition and ECAP. Each parameter was evaluated at varying magnitudes, i.e., 450, 500, and 550 °C for T, 1, 2, and 3 h for t, and 1, 3, and 5% for VF. The effect that process variables had on responses was elucidated using the factorial design with centre point analysis. T and VF were crucial for attaining the optimum ultimate tensile strength (UTS) and microhardness. Reducing VF increased the mechanical properties to 1 vol% of oxide. The maximum hardness of 95 HV was attained at 550 °C, 1.6 h, and 1 vol% ZrO2 with a density of 2.85 g/cm3 and tensile strength of 487 MPa. UTS, density, and microhardness were enhanced by 14%, 1%, and 9.5%, respectively. Additionally, the hot extrusion parameters and ECAP followed by heat treatment strengthened the microhardness by 64% and density by 3%. Compression pressure and extrusion stress produced in these stages were sufficient to eliminate voids that increased the mechanical properties.

Production of Aluminum AA6061 Hybrid Nanocomposite from Waste Metal Using Hot Extrusion Process: Strength Performance and Prediction by RSM and Random Forest.

To date, various studies have analysed the effects of reinforced ceramic on the properties of AA6061 recycled aluminum alloy chips, such as the tensile strength and fractography. However, a comprehensive analysis of the properties of hybrid composite with the addition of nano-silica oxide and nano-copper oxide reinforcements is still very limited. Therefore, this study aimed to optimise the factors comprising the preheating temperature (PHT), preheating time (PHti), and volume fraction (VF) of reinforcements then determine their impacts on the physical and mechanical properties of the recycled solid-state extruded composite aluminum chips. A total of 45 specimens were fabricated through the hot extrusion technique. The response surface methodology (RSM) was employed to study the optimisation at a PHT range of 450-550 °C with PHti of 1-3 h and VF of 1-3 vol% for both reinforcements (SiO2 and CuO). Moreover, a random forest (RF) model was developed to optimize the model based on a metaheuristic method to improve the model performance. Based on the experimental results the RF model achieve better results than response surface methodology (RSM). The functional quadratic regression is curvature and the tested variable shows stable close data of the mean 0 and α2. Based on the Pareto analysis, the PHT and VF were key variables that significantly affected the UTS, microhardness, and density of the product. The maximum properties were achieved at an optimum PHT, PHti, and VF of 541 °C, 2.25 h, 1 vol% SiO2 and 2.13 vol% CuO, respectively. Furthermore, the morphological results of the tensile fractured surface revealed the homogenous distribution of nano-reinforced CuO and SiO2 particles in the specimens' structure.

Conjectured the Behaviour of a Recycled Metal Matrix Composite (MMC⁻AlR) Developed through Hot Press Forging by Means of 3D FEM Simulation.

Melting aluminium waste to produce a secondary bulk material is such an energy-intensive recycling technique that it also indirectly threatens the environment. Hot press forging is introduced as an alternative. Mixing the waste with another substance is a proven practice that enhances the material integrity. To cope with the technology revolution, a finite element is utilised to predict the behaviour without a practical trial. Utilising commercial software, DEFORM 3D, the conjectures were demonstrated scientifically. The flow stress of the material was modified to suit the material used in the actual experiment. It is acknowledged that the stress⁻strain had gradually increased in each step. Due to the confined forming space, the temperature decreased by ~0.5% because the heat could not simply vacate the area. A reduction of ~10% of the flesh observed in the simulation is roughly the same as in the actual experiment. Above all, the simulation abides by the standards and follows what has been done previously. Through the finite element utilisation, this study forecasted the performance of the recycled composite. The results presented may facilitate improvement of the recycling issue and conserve the environment for a better future.