Sustainable face milling of banana peel ash- and mango seed shell ash-reinforced aluminum hybrid composites using RSM–fuzzy LMAW–fuzzy MARCOS

This study addresses the need for sustainable manufacturing practices by exploring the potential of agro-waste-derived materials, specifically Banana Peel Ash (BPA) and Mango Seed Shell Ash (MSSA), as reinforcements in aluminum hybrid composites for face-milling applications. The motivation is to transform agro-waste into value-added materials that enhance machinability, productivity, and sustainability. Aluminum-based hybrid composites were developed using BPA and MSSA, and face-milling experiments were performed with four key input factors: cutting speed, feed rate, depth of cut, and flute cutter angle. Response Surface Methodology (RSM) was employed to model process-response relationships, while triangular fuzzy numbers were used in the Fuzzy LMAW method for determining response weights. The Fuzzy MARCOS method was applied to multi-criteria decision-making to rank machining alternatives. The study revealed that the proposed composite materials exhibit promising machinability under controlled face-milling conditions. The process showed significant sensitivity to machining parameters, with surface roughness (Ra) ranging from 0.37 to 1.12 μm, material removal rate (MRR) ranging from 495 to 4395 mm³/min, power consumption (Pc) ranging from 179 to 369 W, and cutting force (CF) ranging from 60 to 130 N. The optimal machining conditions were determined based on a combination of low Ra, low CF, and Pc, and high MRR. The study’s limitations include the focus on specific composition ranges and machining parameters, as well as the exclusion of microstructural evolution, tool wear, and long-term performance. Future work could expand on these aspects to further validate the findings. The findings suggest that BPA- and MSSA-reinforced aluminum hybrid composites can be effectively utilized in sustainable machining applications. The proposed hybrid optimization framework can assist manufacturers in selecting optimal face-milling conditions, enhancing productivity without compromising surface quality. This research contributes to the novel integration of agro-waste materials in hybrid composites for sustainable manufacturing. The combination of RSM with Fuzzy LMAW and Fuzzy MARCOS decision-making methods provides a robust, multi-response optimization approach for machining performance and sustainability.