Sustainable meso-conical cup fabrication using recycled e-waste-derived copper: a hybrid RSM–Spherical Fuzzy AHP–fuzzy GRA optimization approach

This study investigates meso-conical cup fabrication using as-received copper (AR) and a recycled copper-based composite feedstock (EW) containing 30 wt.% recovered e-waste-derived copper and 70 wt.% as-received copper. To achieve this, we developed a hybrid Response Surface Methodology (RSM)–Spherical Fuzzy AHP–Fuzzy Grey Relational Analysis (GRA) framework in which feed rate, depth, step size, and material type were treated as control factors. At the same time, surface roughness, dimensional accuracy, production cost and energy consumption were selected as response variables. The findings revealed a pronounced quality–cost–energy trade-off. The A14 condition (AR, 20 mm/min feed, 0.15 mm depth, and 0.10 mm step size) delivered the best quality performance, achieving 1.0 µm surface roughness and 97.0% dimensional accuracy. In contrast, the A10 condition (EW, 30 mm/min feed, 0.15 mm depth, and 0.10 mm step size) had lower production cost (₹6.383/part) and energy consumption (2.289 Wh/part) than A14 (₹9.291/part and 3.294 Wh/part). Relative to A10, A14 improved surface roughness by 28.57% and dimensional accuracy by 1.57%, but increased cost by 45.56% and energy use by 43.91%. The results show that partially incorporating recovered e-waste-derived copper is technically feasible and can reduce production cost and operational energy demand under selected conditions. However, the AR condition remains preferable when surface finishes and dimensional accuracy are the primary requirements.