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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., Competing Interests: Acknowledgment (The authors extend their appreciation to King Saud University for funding this work through Researchers Supporting Project number (RSPD2023R711), King Saud University, Riyadh, Saudi Arabia.) This research was funded by King Saud University through Researchers Supporting Project number (RSPD2023R711). This research was supported by Universiti Tun Hussein Onn Malaysia (UTHM) through Tier 1 (Q390). (Communication of this research is made possible through monetary assistance by Universiti Tun Hussein Onn Malaysia and the UTHM Publisher’s Office via Publication Fund E15216. The authors would also like to express the most profound appreciation for supplementary provisions provided by Sustainable Manufacturing and Recycling Technology, Advanced Manufacturing and Materials Center (SMART-AMMC), Universiti Tun Hussein Onn Malaysia)., (Copyright: © 2024 Altharan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Direct hot extrusion is an alternative process for recycling aluminium without melting the scrap. It utilizes low energy and is environmental friendly. This paper reports the microhardness and microstructure of aluminium alloy chips when subjected to various settings of preheating temperature and preheating time in hot extrusion process. Three values of preheating temperature are taken as 450 °C, 500 °C, and 550 °C. On the other hand, three values of preheating time were chosen (1 h, 2 h, 3 h). The influences of the process parameters (preheating temperature and time) are analyzed using design of experiments approach whereby full factorial design with center point analysis are adopted. The total runs are 11 and they comprise of two factors of full factorial design with 3 center points. The responses are microhardness and microstructure. The results show that microhardness increases with the decrease of the preheating temperature. The results also show that the preheating temperature is more important to be controlled rather than the preheating time in microhardness analyses. The profile extrudes at 450 °C and 1 hour has gained the optimum microhardness and it can be concluded that setting temperature at 550 °C for 3 hours results in the highest responses for average grain sizes in analysis of microstructure. [ABSTRACT FROM AUTHOR]