Authors
S P Sundar Singh Sivam, Stalin Kesavan, P Sathishkumar
Published in
Scientific reports. Jul 12, 2026. Epub Jul 12, 2026.
Abstract
Recycled copper from electronic waste offers a sustainable alternative to primary copper production, yet its downstream conversion into rolled sheets for advanced forming applications remains insufficiently explored. This study evaluates recycled copper recovered from discarded air-conditioning units as a feedstock for incremental sheet metal forming (ISMF). The recovered copper scrap was cleaned, melted, cast, rolled, annealed, and processed into thin sheets before CNC-based ISMF trials. Four input process parameters were considered: feed rate 15-45 mm/min, tool depth 0.10-0.15 mm, step size 0.10-0.20 mm, and number of rolling passes six and eight passes. Their effects on surface roughness, thermal conductivity, microhardness, and energy efficiency were investigated using a D-optimal response surface methodology. Multi-response optimization was performed using a hybrid Fuzzy AHP-Fuzzy GRA framework, while model reliability was assessed through ANOVA, adjusted R², predicted R², residual diagnostics, and confirmation experiments. Microstructural observations revealed refined, uniform grains with retained face-centered cubic crystallinity after rolling and annealing. The recycled copper sheets achieved a tensile strength of approximately 300 MPa and hardness values of 96.4-99.7 BHN, confirming their suitability for ISMF. The optimized parameter combination was a feed rate of 30 mm/min, a tool depth of 0.10 mm, a step size of 0.10 mm, and eight rolling passes. Under this condition, the process produced a minimum surface roughness of 1.038 μm, thermal conductivity of 355.68 W/m·K, acceptable hardness, and improved energy performance. Confirmation results showed close agreement between predicted and experimental responses, supporting the reliability of the proposed optimization framework. The work establishes an integrated route for converting e-waste-derived copper into ISMF-ready sheet products. It demonstrates the potential of hybrid fuzzy multi-response optimization for sustainable manufacturing applications.
PMID:
42437821
Bibliographic data and abstract were imported from PubMed on 13 Jul 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 2
- Comments 0