The optimal conditions of applied factors to reuse Aluminium AA6061 scraps are (450, 500, and 550) ⁰C preheating temperature, (1–15) % Boron Carbide (B₄C), and Zirconium (ZrO₂) hybrid reinforced particles at 120 min forging time via Hot Forging (HF) process. The response surface methodology (RSM) and machine learning (ML) were established for the optimisations and comparisons towards materials strength structure. The Ultimate Tensile Strength (UTS) strength and Microhardness (MH) were significantly increased by increasing the processed temperature and reinforced particles because of the material dispersion strengthening. The high melting point of particles caused impedance movements of aluminium ceramics dislocations which need higher plastic deformation force and hence increased the material's mechanical and physical properties. But, beyond Al/10 % B₄C + 10 % ZrO₂ the strength and hardness were decreased due to more particle agglomeration distribution. The optimisation tools of both RSM and ML show high agreement between the reported results of applied parameters towards the materials' strength characterisation. The microstructure analysis of Field Emission Scanning Electron Microscopy (FE-SEM) and Atomic Force Microscope (AFM) provides insights mapping behavioural characterisation supports related to strength and hardness properties. The distribution of different volumes of ceramic particle proportion was highlighted. The environmental impacts were also analysed by employing a life cycle assessment (LCA) to identify energy savings because of its fewer processing steps and produce excellent hybrid materials properties.

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 (A_S: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 A_S: V. The Tp had the largest contributing effect ratio on the UTS, followed by HT and A_S: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.

Medical components made of titanium, steels, ceramic, and aluminium produced by metal injection moulding require different machining processes and creating a custom mould for each patient will limit the mould’s flexibility. This research aimed at developing a Polylactic acid (PLA)/Stainless Steel (SS316L) composite filament for 3D printing and investigating the influence of the compounding ratio on the mechanical properties of PLA/SS 316L polymer composite printed by Fused Deposition Modelling (FDM) machine. The effects of SS316L content and melting temperature on tensile strength and impact strength of printed samples were analysed at 2%, 7%, and 12% weight percentage (wt.%) and 200°C, 210°C, and 220°C respectively. The SS 316L powder was added to PLA by weight percentage (wt.%), and 0.4 mm diameter nozzle was utilized during printing. At a 12% addition of SS316L, the tensile strength (TS) and Charpy impact strength (IS) were maximised to 52.832 MPa and 0.1275 kJ/m² respectively. A decreasing trend was observed for both properties with 2% and 7% of SS 316L addition. Moreover, when the temperature was set to 220°C, the TS increased for all composites regardless of the weight percentage. The optimized parameter setting by RSM was 12 wt.% and 220°C revealed the TS and IS at 54.04 MPa and 0.172 kJ/m². The errors between the predicted and experimental values for TS and IS were 1.4% and 4.65%.