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

Chaudhari, Rakesh; Shah, Yug; Khanna, Sakshum; Patel, Vivek; Vora, Jay; Pimenov, Danil Yurievich; Giasin, Khaled

doi:10.3390/ma15207392

Cited by 12 publications

(6 citation statements)

References 55 publications

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“…The culmination of this meticulous procedure yielded the desired Al 2 O 3 nanopowder, which could subsequently be utilized for a myriad of applications. The average size of the alumina nanopowder was observed to be ~110 nm, which was near to our previously reported work [42]. X-ray diffraction spectroscopy (XRD) was used to confirm the structural formation of alumina.…”

Section: Synthesis Of Nanopowderssupporting

confidence: 79%

“…We utilized a hydrothermal synthesis approach to generate aluminum oxide (Al 2 O 3 ) nanopowder without the preliminary purification of chemical reagents [42] A hydrothermal synthesis approach was employed without the prior purification of chemical reagents to produce aluminum oxide (Al 2 O 3 ) nanopowder. The key reagents utilized in this process encompassed citric acid, aluminum nitrate nanohydrate, triethanolamine, and ethylene glycol.…”

Section: Synthesis Of Nanopowdersmentioning

confidence: 99%

“…Chaudhari et al [42] analyzed the impact of alumina powder amount on MRR, tool wear rate (TWR), and SR through the die-sinking EMD process of Nitinol. The amounts of alumina powder, T off , and T on were detected as vital input factors to have a significant impact on all output measures.…”

Section: Introductionmentioning

confidence: 99%

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

Chaudhari,

Khanna,

Patel

et al. 2023

Micromachines

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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.

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Section: Synthesis Of Nanopowderssupporting

confidence: 79%

Section: Synthesis Of Nanopowdersmentioning

confidence: 99%

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

Chaudhari,

Khanna,

Patel

et al. 2023

Micromachines

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“…Discharge energy generated during the process creates a larger amount of debris. This further generates deeper and wider craters on the machined surface specimens, and also depreciates the work surface [75]. As a result, the surface layer becomes rough, increasing the SR. As per Figure 8b, current and T on had negative effects on the surface quality.…”

Section: Effect Of Machining Variables On Responsesmentioning

confidence: 98%

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

et al. 2022

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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, Toff, and Ton 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.

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“…A high-quality PCD skiving cutter was obtained with an Rt of 5.6 µm and no phase transition damage. Rakesh Chaudhari et al [ 11 ] experimentally investigated the effect of alumina (Al2O3) nano-powder on the electrical discharge machining (EDM) process of a Nitinol shape memory alloy (SMA), and the related parameters were optimized via ANOVA analysis. Lida Heng et al [ 12 ] summarized the recent advances in non-conventional finishing processes for difficult-to-machine ceramics.…”

mentioning

confidence: 99%

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

et al. 2023

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

Cited by 12 publications

References 55 publications

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

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

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

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

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