Study on productivity and aerosol emissions of magnetic field-assisted EDM process of SiCp/Al composite with high volume fractions. (10th April 2021)

• Record Type: Journal Article
• Authors: Zhang, Zhen; Zhang, Yi; Lin, Liquan; Wu, Jinhong; Yu, Haishen; Pan, Xin; Li, Guangliang; Wu, Jie; Xue, Tao
• Is Part Of: Journal of cleaner production. Volume 292(2021)
• Publication Date: 2021-04-10
• Subjects: EDM -- SiCp/Al Composite -- Aerosol emissions -- Material removal rate -- Electrode wear rate -- Magnetic field; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2021.126018
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: SiC particulate reinforced Al-based metal matrix composites with high volume fractions ( HVF − SiC p / Al ) is widely applied in many engineering fields due to combining outstanding properties of both metal and ceramic materials. It's a tough problem to process HVF − SiC p / Al with superior machining performance and minor environmental effect. Thus, in this paper, magnetic field assisted electrical discharge machining (MF-EDM) of HVF − SiC p / Al is proposed to improve the sustainable machining performance including productivity and aerosol emissions which is most harmful to operators' health. Based on Taguchi method, a set of experiments are settled to investigate materials removal rate (MRR), electrode wear rate (EWR), and aerosol emissions under MF-EDM process of 45% and 65% SiC p / Al . It shows that pulse current is the major factor, and magnetic field assisted technology significantly develops the surface integrity whereas it just slightly contributes to improve MRR, EWR, and aerosol emissions when the intensity of magnetic is in the range of 0.1T–0.2T. Additionally, an optimization algorithm combing Quantum-behaved Particle Swarm Optimization with Gaussian distributed local attractor (GAQPSO) and Back Propagation Neural Network (BPNN) is employed to provide optimal machining parameters for economic and environmental MF-EDM process of HVF − SiC p / Al . Compared to the average experimental data, for 45% SiC p / Al, the average optimal solutions of EWR, and aerosol emissions were decreased by about 10% and 15% whereas MRR was increased by about 6.6%; for 65% SiC p / Al, the average optimal solutions of EWR, and aerosol emissions were decreased by about 5.7% and 10% whereas MRR was increased about by 5.5%. It presents an effective work for EDM process of HVF − SiC p / Al with high sustainable performance. Highlights: Magnetic field assisted EDM of HVF-SiCp /Al is proposed to improve productivity and aerosol emissions. Material removal rate, electrode wear rate, aerosol emissions, and surface integrity of MF-EDM were completely investigated. The composition of emitted aerosols from MF-EDM of HVF-SiCp /Al is analyzed. MF-EDM process of HVF-SiCp /Al is optimized economically and environmentally by BPNN-GAQPSO method. Optimal parameter combinations for MF-EDM process of 45% and 65% SiCp /Al are recommended.