Optimization of AA7075–SiC Composite Machining by WEDM Using Biosilica Additives

The study herein discusses the wire-cut electrical discharge machining (WEDM) with the addition of biosilica from maize cobs for the precision cutting of AA7075 aluminum and silicon carbide (SiC) metal matrix composites. The new, harmless addition of biosilica as a dielectric agent not only supports the sustainability of the process but also enhances surface quality and cutting speed. A Taguchi L9 design was used to conduct an experiment investigating the effects of peak current, gap voltage, and pulse-on time on material removal rate (MRR) and surface roughness (Ra). The optimal machining parameters were determined using Grey Relational Analysis and an artificial neural network (ANN). These model developments aimed to predict performance outcomes. The findings indicated that the dielectric fluid with biosilica increased MRR by 25% and simultaneously decreased Ra by 15% when compared with the typical dielectric. SEM and AFM analysis confirmed surface uniformity improvement and reduced microcrack formation. The artificial neural network model, trained using the backpropagation method on the experimental data, produced predictions for material removal rate and average roughness with an R² of 0.96, indicating that the model is highly reliable. In conclusion, the present research not only reveals a non-conventional machining process but also provides an eco-friendly approach to optimizing wire EDM of metal matrix composites with nano-reinforcement.