Effect of multi-walled carbon nanotubes on the performance evaluation of nickel-based super-alloy–Udimet 720 machined using WEDM process

Abstract

The diverse capabilities of nickel-based super-alloy (Udimet 720), like robust mechanical strength, ductility, resistance to excessive temperature deformation, and advanced corrosion and oxidation resistance, make it suitable for use in multiple applications. These super-alloys are identified as extremely difficult materials for machining to meet feature and manufacturing requirements. In the present work, we demonstrated the machining of Udimet 720 by employing the wire-electrical discharge machining (WEDM) technique. Pulse-on-time (Ton), pulse-off-time (Toff), current, and MWCNT amount were preferred as input variables. The effect of selected design variables was studied on material removal rate (MRR), surface roughness (SR), and recast layer thickness (RLT). Box-Behnken design was utilized to design an experimental matrix. For statistical analysis, analysis of variance (ANOVA) was employed. From ANOVA, the current had the highest contributor with 35.85% to affect MRR, while MWCNT amount was found to be the highest contributor for deciding the values of both SR and RLT with contributions of 42.66% and 40.07%, respectively. The addition of MWCNT at 1 g/L has substantially improved MRR from 0.8546 to 1.2199 g/min, SR reduced from 5.88 µm to 2.98 µm, and reduction in RLT from 17.8 to 11.61 µm. The passing vehicle search (PVS) algorithm was implemented, and the results of single-objective optimization presented the largest MRR of 1.8883 g/min, least SR of 1.89 µm, and least RLT of 9.70 µm. Additionally, a set of non-dominated solutions was obtained through Pareto optimal fronts. A small acceptable deviation was detected among the actual and forecasted results from PVS algorithm. It clearly reveals the acceptance of the PVS technique in the present study for Udimet 720. Lastly, the significance of MWCNT amount on surface textures was revealed by employing scanning electron microscopy (SEM).

Predictive modelling framework on the basis of artificial neural network: A case of nano-powder mixed electric discharge machining

“… Reference Methodology Adopted Improvements of this study Nain et al [ 29 ] Used SVM to predict the MRR and SR The MRR improved by 74.75 %, and SR 63.63 % Varun and Venkaiah [ 30 ] GRA coupled with GA The MRR enhanced by 95 %. Chaudhari et al [ 36 ] Optimization using PVS Algorithm The MRR improved by 98 %, however, SR depreciated by 60.94 % Chaudhari et al [ 37 ] Optimization using PVS Algorithm The MRR enhanced by 97.55 % and SR depreciated by 53.37 % …”

“…Chaudhari et al [ 36 ] used MWCNT for the WEDM of Ni-based superalloy (Udimet 720) by incorporating various input parametric settings to measure the MRR, SR and recast layer thickness (RLT). The authors concluded that by feeding the MWCNT in the dielectric during WEDM process enhanced the MRR by 35.85 %, reduced the SR and RLT by 42.66 % and 40.07 %, respectively.…”

Multi-Response Optimization and Influence of Expanded Graphite on Performance of WEDM Process of Ti6Al4V

“…One such non-traditional process widely preferred for machining difficult-to-cut materials such as Ti6Al4V is the wire electrical discharge machining (WEDM) process. In the WEDM process, the workpiece and wire electrode produce a sequence of discrete sparks that erode the material from the workpiece [19,20]. A thin layer of dielectric fluid is continuously delivered to the machining zone to flush away the eroded particles.…”

Advanced Optimization of Surface Characteristics and Material Removal Rate for Biocompatible TI6Al4V using WEDM Process with BBD and NSGA II

“…In several industries, wire electric discharge machining (WEDM) which utilizes thermo-mechanical energy can process with excellent accuracy and provide a good surface finish, is often employed to deal with such high-strength materials [13][14][15]. In the WEDM process, a conductive wire (electrode) that travels continually and the heat results in an electric spark which erodes the conductive work material [16,17]. During the process, dielectric fluid is utilized as a medium for ionization to create the electrical arc across the workpiece and the wire (electrode).…”