ArticleScientific reports2026
Hybrid fuzzy AHP-WASPAS optimization of turning parameters for electronic waste-derived aluminum alloys: advancing sustainable machining in line with sustainable development goals and circular manufacturing.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This study presents a sustainable machining optimization framework for waste-derived Al-Cu-Mg alloys reinforced with zirconium dioxide (ZrO₂). A hybrid Fuzzy Analytic Hierarchy Process-Weighted Aggregated Sum Product Assessment framework was applied to optimize turning parameters, including cutting speed of 11-42 m/min, feed rate of 0.05-0.15 mm/rev, and depth of cut of 0.5-1.0 mm. Multiple machining responses were evaluated, including surface roughness, material removal rate, tool wear, power consumption, dimensional accuracy, specific cutting energy, and chip volume. Three die-cast alloys were fabricated from recovered metallic waste streams: Sample A with 91% Al, 4.5% Cu, 1.8% Mg, and 2% ZrO₂; Sample B with 87.3% Al, 4.9% Cu, 1.8% Mg, and 6% ZrO₂; and Sample C with 82.5% Al, 5.5% Cu, 2% Mg, and 10% ZrO₂. The experimental trials were planned using a D-optimal Response Surface Methodology design, and the machining alternatives were ranked using the hybrid Fuzzy AHP-WASPAS model. The final ranking identified Alternative 8, corresponding to Sample B with 6 wt.% ZrO₂, as the overall optimum condition because it provided the best compromise among surface quality, productivity, tool wear, energy demand, dimensional accuracy, and material utilization. Compared with the unoptimized baseline condition, the optimum condition improved surface finish by 25%, increased material removal rate by 30%, and reduced tool wear by 15%. The superior performance of Sample B is attributed to balanced ZrO₂-induced grain refinement, improved reinforcement dispersion, reduced agglomeration, and stable tool-workpiece interaction. Although Run 3 showed the best energy-specific response, it was not the overall optimum because the final decision was based on simultaneous multi-response optimization. The proposed framework demonstrates a practical route for converting waste-derived aluminum alloy streams into value-added machinable composites while supporting energy-efficient and circular manufacturing aligned with SDG 9 and SDG 12.
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