Multi-Objective Optimization of Electrical Discharge Machining Parameters for 2024 Aluminum Alloy Using Grey-Taguchi Method

摘要

This paper focused on Grey relational analysis (GRA) to optimize EDM parameters through multi-objective optimization for Al2024 aluminum and electrode graphite ISO-63 was used as a cutting tool. The process parameters pulse on time, duty factor, pulse current and open voltage. Performance characteristics examined included material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). Taguchi's 27 experimental designs, often called an orthogonal array (OA), was utilized to ignore interaction and concentrate on main effect estimation. GRA was performed to optimize input parameters levels. Results were that MRR increased from 35.00 to 35.11 mm~3/min, EWR decreased from 11.63 to 10.89 mm~3/min, and SR decreased from 5.01 to 4.97 μm. Taguchi and GRA resulted in clear improvements in MRR, EWR, and SR.