The experimental research presented in this article explores the wire electrical discharge machining of Monel 400 alloy. An L-18 orthogonal array has been used for experimentation by considering machine controllable factors (i.e. wire tension, pulse-on time, pulse frequency, peak current and servo voltage) and machine uncontrollable factors (namely flushing nozzle height, workpiece thickness and corner angle) as process parameters. Using Taguchi methodology, the influence of the process parameters on the responses, such as material removal rate, surface roughness and corner error, were studied. The impact of pulse parameters modification in corner accuracy improvement has been analyzed. Finally, using Taguchi’s additive model predictions and Pareto optimality approach, a sample technology table for a specific machining condition has been reported for ready use.

In this work, wire electrical discharge machining (WEDM) of aluminum (LM25) reinforced with fly ash and boron carbide (B4C) hybrid composites was performed to investigate the influence of reinforcement wt% and machining parameters on the performance characteristics. The hybrid composite specimens were fabricated through the stir casting process by varying the wt% of reinforcements from 3 to 9. In the machinability studies, the WEDM process control parameters such as gap voltage, pulse-on time, pulse-off time, and wire feed were varied to analyze their effects on machining performance including volume removal rate and surface roughness. The WEDM experiments were planned and conducted through the L27 orthogonal array approach of the Taguchi methodology, and the corresponding volume removal rate and surface roughness were measured. In addition, the multi-parametric ANOVA was performed to examine the statistical significance of the process control parameters on the volume removal rate and surface roughness. Furthermore, the spatial distribution of the parameter values for both the responses were statistically analyzed to confirm the selection of the range of the process control parameters. Finally, the quadratic multiple linear regression models (MLRMs) were formulated based on the correlation between the process control parameters and output responses. The Grass–Hooper Optimization (GHO) algorithm was proposed in this work to identify the optimal process control parameters through the MLRMs, in light of simultaneously maximizing the volume removal rate and minimizing the surface roughness. The effectiveness of the proposed GHO algorithm was tested against the results of the particle swarm optimization and moth-flame optimization algorithms. From the results, it was identified that the GHO algorithm outperformed the others in terms of maximizing volume removal rate and minimizing the surface roughness values. Furthermore, the confirmation experiment was also carried out to validate the optimal combination of process control parameters obtained through the GHO algorithm.

A natural cellulosic filler extracted from the seed shells of the Putranjiva roxburghii W. has been investigated for its suitability in reinforcement of fiber reinforced polymers. The physicochemical, morphological, structural, and thermal properties of untreated and alkali-treated Putranjiva roxburghii seed shell filler (PRSSF) particles are investigated for the first time. The particle size and morphology of PRSSF particles have been analyzed using laser particle size analyzer and field emission scanning electron microscopy. Energy-dispersive X-ray spectroscopy was used to validate the elements present on the untreated and treated PRSSF particles. The structural features were investigated using X-ray Diffraction, nuclear magnetic resonance, and Fourier transform infrared spectroscopy analysis, which revealed the reduction of the amorphous contents and noncellulosic components. Thermogravimetric analysis was employed to determine the thermal stability of both untreated and treated PRSSF particles. The results indicated that alkali-treated PRSSF particles have higher thermal degradability and stability than untreated PRSSF particles.