Experimental Investigations and Effect of Nano-Powder-Mixed EDM Variables on Performance Measures of Nitinol SMA

Experimental Investigations of Using Aluminum Oxide (Al2O3) and Nano-Graphene Powder in the Electrical Discharge Machining of Titanium Alloy

In the present study, a comprehensive parametric analysis was carried out using the electrical discharge machining of Ti6Al4V, using pulse-on time, current, and pulse-off time as input factors with output measures of surface roughness and material removal rate. The present study also used two different nanopowders, namely alumina and nano-graphene, to analyze their effect on output measures and surface defects. All the experimental runs were performed using Taguchi's array at three levels. Analysis of variance was employed to study the statistical significance. Empirical relations were generated through Minitab. The regression model term was observed to be significant for both the output responses, which suggested that the generated regressions were adequate. Among the input factors, pulse-off time and current were found to have a vital role in the change in material removal rate, while pulse-on time was observed as a vital input parameter. For surface quality, pulse-on time and pulse-off time were recognized to be influential parameters, while current was observed to be an insignificant factor. Teaching-learning-based optimization was used for the optimization of output responses. The influence of alumina and nano-graphene powder was investigated at optimal process parameters. The machining performance was significantly improved by using both powder-mixed electrical discharge machining as compared to the conventional method. Due to the higher conductivity of nano-graphene powder, it showed a larger improvement as compared to alumina powder. Lastly, scanning electron microscopy was operated to investigate the impact of alumina and graphene powder on surface morphology. The machined surface obtained for the conventional process depicted more surface defects than the powder-mixed process, which is key in aeronautical applications.

Analyzing the Relationship between the Chemical Composition and the Surface Finish of Alnico Alloys in EDM

The purpose of this study was to determine whether the chemical compositions of Alnico alloys had any effects on the electrical discharge machining (EDM) performance and the surface finish. This article compares the behavior of three different Alnico alloys in electrical discharge machining. The experiments were conducted under different conditions using a BP93L EDM machine (ZAP BP, Końskie, Poland), applying an additional rotary motion to the electrode. A Box-Behnken experimental design was employed to analyze the influence of three factors, i.e., the spark current, the pulse-on time, and the pulse-off time, at three levels for three Alnico alloys. The material removal rate (MRR) was calculated for the different process parameters. After the EDM, the surface roughness was studied using a Talysurf CCI Lite non-contact profiler (Taylor-Hobson, Leicester, UK). The next step of the experiments involved preparing metallographic specimens to be observed by means of scanning electron microscopy (SEM) and optical microscopy (OM). Measurements of the nanohardness were also performed. The experimental data were then analyzed using Statistica software version 10 (64-bit) to determine and graphically represent the relationships between the input and output parameters for the three Alnico alloys. The chemical compositions of the Alnico alloys affected the thickness of the white layer (higher cobalt content, lower white layer thickness) and the material removal rate. The higher the cobalt content, the thinner the white layer and the lower the material removal efficiency. Moreover, the cobalt content in Alnico alloys influenced the shape of the precipitates; these ranged from spheroidal (13% Co) to mix-shaped (21.3% Co) to flake-shaped (32.2%). The hardness of the resulting white layer was 874 HV at10 mN.

Ultra-Precision Manufacturing Technology for Difficult-to-Machine Materials

Ultra-precision manufacturing requires superior components with an impeccable surface finish and accuracy [...].

Implementation of Passing Vehicle Search Algorithm for Optimization of WEDM Process of Nickel-Based Superalloy Waspaloy

Nickel-based superalloys find their main use in missile engines, atomic devices, investigational aircraft, aerospace engineering, industrial applications, and automotive gas turbines, spacecraft petrochemical tools, steam power, submarines, and broader heating applications. These superalloys impose certain difficulties during the process fabrication owing to their levels of higher hardness. In the current study, the precise machining of Waspaloy was attempted through the wire electrical discharge machining (WEDM) technique. A multi-objective optimization has been performed, and the influence of multi-walled carbon nanotubes (MWCNTs) has been assessed using the passing vehicle search (PVS) algorithm. The effects of machining variables like current, T_off, and T_on were studied using the output measures of material removal rate (MRR), recast layer thickness (RLT), and surface roughness (SR). The Box-Behnken design was applied to generate the experimental matrix. Empirical models were generated which show the interrelationship among the process variables and output measures. The analysis of variance (ANOVA) method was used to check the adequacy, and suitability of the models and to understand the significance of the parameters. The PVS technique was executed for the optimization of MRR, SR, and RLT. Pareto fronts were derived which gives a choice to the user to select any point on the front as per the requirement. To enhance the machining performance, MWCNTs mixed dielectric fluid was utilized, and the effect of these MWCNTs was also analyzed on the surface defects. The use of MWCNTs at 1 g/L enhanced the performance of MRR, SR, and RLT by 65.70%, 50.68%, and 40.96%, respectively. Also, the addition of MWCNTs has shown that the machined surface largely reduces the surface defects.