Multi-response Optimization and Effect of Alumina Mixed with Dielectric Fluid on WEDM Process of Ti6Al4V

Vora, Jay; Prajapati, Nisarg; Patel, Smit; Sheth, S.M.; Patel, Aditya; Khanna, Sakshum; Ayesta, I.; Lacalle, Luis Norberto López de; Chaudhari, Rakesh

doi:10.1007/978-981-16-7660-4_25

Cited by 16 publications

(9 citation statements)

References 25 publications

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“…A confidence level of 5% was employed to investigate the effect of design variables [ 58 ]. To have a significance of an input variable on the output variable, it is desired to have the P-value be less than 0.05 [ 59 , 60 ]. Table 2 shows the ANOVA for the response measure of MRR.…”

Section: Resultsmentioning

confidence: 99%

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy

et al. 2022

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Nitinol-shape memory alloys (SMAs) are widely preferred for applications of automobile, biomedical, aerospace, robotics, and other industrial area. Therefore, precise machining of Nitinol SMA plays a vital role in achieving better surface roughness, higher productivity and geometrical accuracy for the manufacturing of devices. Wire electric discharge machining (WEDM) has proven to be an appropriate technique for machining nitinol shape memory alloy (SMA). The present study investigated the influence of near-dry WEDM technique to reduce the environmental impact from wet WEDM. A parametric optimization was carried out with the consideration of design variables of current, pulse-on-time (Ton), and pulse-off-time (Toff) and their effect were studied on output characteristics of material removal rate (MRR), and surface roughness (SR) for near-dry WEDM of nitinol SMA. ANOVA was carried out for MRR, and SR using statistical analysis to investigate the impact of design variables on response measures. ANOVA results depicted the significance of the developed quadratic model for both MRR and SR. Current, and Ton were found to be major contributors on the response value of MRR, and SR, respectively. A teaching–learning-based optimization (TLBO) algorithm was employed to find the optimal combination of process parameters. Single-response optimization has yielded a maximum MRR of 1.114 mm3/s at Ton of 95 µs, Toff of 9 µs, current of 6 A. Least SR was obtained at Ton of 35 µs, Toff of 27 µs, current of 2 A with a predicted value of 2.81 µm. Near-dry WEDM process yielded an 8.94% reduction in MRR in comparison with wet-WEDM, while the performance of SR has been substantially improved by 41.56%. As per the obtained results from SEM micrographs, low viscosity, reduced thermal energy at IEG, and improved flushing of eroded material for air-mist mixture during NDWEDM has provided better surface morphology over the wet-WEDM process in terms of reduction in surface defects and better surface quality of nitinol SMA. Thus, for obtaining the better surface quality with reduced surface defects, near-dry WEDM process is largely suitable.

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Section: Resultsmentioning

confidence: 99%

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy

et al. 2022

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“…Conversely, in case of the plot for MRR vs. T off , a drop in MRR response was recorded. This was due to the fact that enhancement in the T off results in the drop in discharge energy during the sparking process [73]. Thus, at higher T off values, lower levels of thermal energy are produced.…”

Section: Effect Of Machining Variables On Responsesmentioning

confidence: 99%

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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“…The graph depicts the inverse effect of increasing Toff on MRR. An increase in Toff enlarges the interval between two consecutive sparks, reducing the number of active sparks [50]. Lower discharge energy will be achieved with larger Toff values.…”

Section: Effect Of Toff On Responsesmentioning

confidence: 99%

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

Chaudhari¹,

Ayesta

Doshi³

et al. 2022

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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 g/min to 1.2199 g/min, SR reduced from 5.88 µm to 2.98 µm, and reduction in RLT from 17.8 µm 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).

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Multi-response Optimization and Effect of Alumina Mixed with Dielectric Fluid on WEDM Process of Ti6Al4V

Cited by 16 publications

References 25 publications

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy

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

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

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