ECAR and PM processing of AA2014 aerospace scrap, machine learning-parameter optimization

This study investigates the recycling of aerospace aluminum scrap obtained from a decommissioned aircraft using equal channel angular rolling (ECAR) and powder metallurgy (PM) processing routes. ECAR was performed using dies with channel angles of 90°, 105°, and 120°, along with multiple passes and varying copper shielding thicknesses, to promote grain refinement and enhance strength. The wear and mechanical behavior of the alloy processed through both routes was evaluated. Mechanical characterization revealed a significant improvement in hardness and tensile strength with an increase in the number of passes, with the highest enhancement observed in samples processed using 1 mm copper shielding at a die angle of 90°. The sintered compact exhibited superior mechanical performance, achieving a hardness of 220 HV and a tensile strength of 495 MPa, surpassing the ECAR-processed samples. X-ray diffraction analysis confirmed substantial grain refinement and reduced crystallite size in both processing routes. Machine learning techniques were employed to optimize key processing parameters, enabling data-driven improvement of material performance. The findings establish PM as a sustainable and high-performance approach for recycling aerospace aluminum scrap. The novelty of this work lies in integrating advanced processing techniques with predictive modeling.